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ORCIDLawrence O. Hall
Larry O. Hall – Lawrence O'Higgins Hall
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2020 – today
- 2026
[j75]Nikolai Fetisov, Wai Lone Jonathan Ho
, Ghada Zamzmi, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath:
Detection of Confounders and Potential Confounders in Computed Tomography Lung Datasets. J. Imaging Inform. Medicine 39(4): 3085-3093 (2026)- [c142]Nishat Nayla Labiba, Raahil Patel, Pablo Sanchez-Sotelo, Lawrence O. Hall, Dmitry B. Goldgof, Mark A. Frankle:
Automated Detection of Intraoperative Blood Loss in Shoulder Arthroplasty Using GPT-4o. CBMS 2026: 218-219 - [i12]Abhiram Kandiyana, Ankur Mali, Lawrence O. Hall, Peter R. Mouton, Dmitry B. Goldgof:
A Human-in-the-Loop Framework for Efficient Prompt Selection in Microscopy Vision-Language Models. CoRR abs/2605.20495 (2026) - 2025
- [c141]Abhiram Kandiyana, Peter R. Mouton, Yaroslav Kolinko, Lawrence O. Hall, Dmitry B. Goldgof:
Active Prompt Tuning Enables GPT-4O to do Efficient Classification of Microscopy Images. ISBI 2025: 1-5 - [i11]Md Mushfiqul Islam, Nishat N. Labiba, Lawrence O. Hall, David S. Simmons:
Reducing Data Requirements for Sequence-Property Prediction in Copolymer Compatibilizers via Deep Neural Network Tuning. CoRR abs/2507.21902 (2025) - 2024
- [j74]Saeed S. Alahmari, Lawrence O. Hall, Peter R. Mouton, Dmitry B. Goldgof:
Repeatability of Fine-Tuning Large Language Models Illustrated Using QLoRA. IEEE Access 12: 153221-153231 (2024) - [j73]Adriana Iamnitchi, Lawrence O. Hall, Sameera Horawalavithana, Frederick Mubang, Kin Wai Ng, John Skvoretz:
Modeling information diffusion in social media: data-driven observations. Frontiers Big Data 6 (2024) - [j72]Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
A Review of Nuclei Detection and Segmentation on Microscopy Images Using Deep Learning With Applications to Unbiased Stereology Counting. IEEE Trans. Neural Networks Learn. Syst. 35(6): 7458-7477 (2024) - [c140]Manas Sanjay Pakalapati, Dmitry B. Goldgof, Lawrence O. Hall, Ghada Zamzmi:
Anonymized Identity Tracking: Privacy Preserving Facial Encoding. CBMS 2024: 89-93 - [c139]Abhiram Kandiyana, Peter R. Mouton, Lawrence O. Hall, Dmitry B. Goldgof:
Active Prompting of Vision Language Models for Human-in-the-loop Classification and Explanation of Microscopy Images. CBMS 2024: 205-212 - [i10]Shashwat Kumar, Francis Hahn, Xinming Ou, Dmitry B. Goldgof, Lawrence O. Hall, Jay Ligatti, S. Raj Rajagopalan, Armin Ziaie Tabari:
A Preliminary Study on Using Large Language Models in Software Pentesting. CoRR abs/2401.17459 (2024) - [i9]Abhiram Kandiyana, Peter R. Mouton, Yaroslav Kolinko, Lawrence O. Hall, Dmitry B. Goldgof:
Active Prompt Tuning Enables Gpt-40 To Do Efficient Classification Of Microscopy Images. CoRR abs/2411.02639 (2024) - 2023
- [j71]Kin Wai Ng, Frederick Mubang, Lawrence O. Hall, John Skvoretz, Adriana Iamnitchi:
Experimental evaluation of baselines for forecasting social media timeseries. EPJ Data Sci. 12(1): 8 (2023) - [j70]Frederick Mubang, Lawrence O. Hall:
VAM: An End-to-End Simulator for Time Series Regression and Temporal Link Prediction in Social Media Networks. IEEE Trans. Comput. Soc. Syst. 10(4): 1479-1490 (2023) - [c138]Hunter Morera, Palak Dave, Saeed S. Alahmari, Yaroslav Kolinko, Lawrence O. Hall, Dmitry B. Goldgof, Peter R. Mouton:
MIMO YOLO - A Multiple Input Multiple Output Model for Automatic Cell Counting. CBMS 2023: 827-831 - [c137]Nikolai Fetisov, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath:
Unsupervised Prostate Cancer Histopathology Image Segmentation via Meta-Learning. CBMS 2023: 838-844 - [c136]Palak Dave, Yaroslav Kolinko, Hunter Morera, Kurtis Allen, Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
MIMO U-Net: efficient cell segmentation and counting in microscopy image sequences. Digital and Computational Pathology 2023 - [c135]Frederick Mubang, Lawrence O. Hall:
Using SMOTE-based Data Augmentation for Social Media Time Series Prediction. SMC 2023: 893-898 - 2022
- [j69]Kaoutar Ben Ahmed, Lawrence O. Hall, Dmitry B. Goldgof, Ryan Fogarty:
Achieving Multisite Generalization for CNN-Based Disease Diagnosis Models by Mitigating Shortcut Learning. IEEE Access 10: 78726-78738 (2022) - [j68]Hunter Morera, Roshan Warman, Azubuogu Anudu, Chukwudumebi Uche, Ivana Radosavljevic, Nikhil Reddy, Ahan Kayastha, Niharika Baviriseaty, Rahul Mhaskar, Andrew A. Borkowski, Patrick Brady, Satish Singh, Gerard Mullin, José Lezama, Lawrence O. Hall, Dmitry B. Goldgof, Gitanjali Vidyarthi:
Reduction of Video Capsule Endoscopy Reading Times Using Deep Learning with Small Data. Algorithms 15(10): 339 (2022) - [c134]Frederick Mubang, Lawrence O. Hall:
Simulating New and Old Twitter User Activity with XGBoost and Probabilistic Hybrid Models. ICMLA 2022: 132-139 - [c133]Nikolai Fetisov, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath:
Survival time prediction from unannotated lung cancer histopathology images. Digital and Computational Pathology 2022 - [c132]Hunter Morera, Palak Dave, Yaroslav Kolinko, Kurtis Allen, Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
Classification of global microglia proliferation based on deep learning with local images. Image Processing 2022 - [d1]Kaoutar Ben Ahmed, Gregory M. Goldgof, Rahul Paul, Dmitry B. Goldgof, Lawrence O. Hall:
COVID-19 and Pneumonia Xrays. IEEE DataPort, 2022
- [i8]Frederick Mubang, Lawrence O. Hall:
Simulating User-Level Twitter Activity with XGBoost and Probabilistic Hybrid Models. CoRR abs/2202.08964 (2022) - [i7]Kin Wai Ng, Frederick Mubang, Lawrence O. Hall, John Skvoretz, Adriana Iamnitchi:
Experimental Evaluation of Baselines for Forecasting Social Media Timeseries. CoRR abs/2210.05847 (2022) - 2021
- [j67]Kaoutar Ben Ahmed, Gregory M. Goldgof, Rahul Paul, Dmitry B. Goldgof, Lawrence O. Hall:
Discovery of a Generalization Gap of Convolutional Neural Networks on COVID-19 X-Rays Classification. IEEE Access 9: 72970-72979 (2021) - [c131]Rahul Paul, Sherzod Kariev, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Deep radiomics: deep learning on radiomics texture images. Computer-Aided Diagnosis 2021 - [i6]Kaoutar Ben Ahmed, Lawrence O. Hall, Dmitry B. Goldgof, Gregory M. Goldgof, Rahul Paul:
Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images Based on Confounders. CoRR abs/2102.04300 (2021) - [i5]Subhashis Banerjee, Sushmita Mitra, Lawrence O. Hall:
Analysis of MRI Biomarkers for Brain Cancer Survival Prediction. CoRR abs/2109.02785 (2021) - 2020
- [j66]Saeed S. Alahmari, Dmitry B. Goldgof, Peter R. Mouton, Lawrence O. Hall:
Challenges for the Repeatability of Deep Learning Models. IEEE Access 8: 211860-211868 (2020) - [j65]Rahul Paul, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future. Comput. Biol. Medicine 122: 103882 (2020) - [c130]Valerie Cross, Michael Zmuda, Rahul Paul, Lawrence O. Hall:
Fuzzy Set Similarity for Feature Selection in Classification. FUZZ-IEEE 2020: 1-8 - [c129]Rahul Paul, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Mitigating Adversarial Attacks on Medical Image Understanding Systems. ISBI 2020: 1517-1521 - [c128]Renhao Liu, Frederick Mubang, Lawrence O. Hall:
Simulating Temporal User Activity on Social Networks with Sequence to Sequence Neural Models. SMC 2020: 1677-1684 - [i4]Lawrence O. Hall, Rahul Paul, Dmitry B. Goldgof, Gregory M. Goldgof:
Finding Covid-19 from Chest X-rays using Deep Learning on a Small Dataset. CoRR abs/2004.02060 (2020)
2010 – 2019
- 2019
- [c127]Rahul Paul, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Towards deep radiomics: nodule malignancy prediction using CNNs on feature images. Computer-Aided Diagnosis 2019: 109503Z - [c126]Kaoutar Ben Ahmed, Lawrence O. Hall, Renhao Liu, Robert A. Gatenby, Dmitry B. Goldgof:
Neuroimaging Based Survival Time Prediction of GBM Patients Using CNNs from Small Data. SMC 2019: 1331-1335 - [c125]Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
Automatic Cell Counting using Active Deep Learning and Unbiased Stereology. SMC 2019: 1708-1713 - [c124]Renhao Liu, Frederick Mubang, Lawrence O. Hall, Sameera Horawalavithana, Adriana Iamnitchi, John Skvoretz:
Predicting Longitudinal User Activity at Fine Time Granularity in Online Collaborative Platforms. SMC 2019: 2535-2542 - [c123]Sameera Horawalavithana, Abhishek Bhattacharjee, Renhao Liu, Nazim Choudhury, Lawrence O. Hall, Adriana Iamnitchi:
Mentions of Security Vulnerabilities on Reddit, Twitter and GitHub. WI 2019: 200-207 - [i3]Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Palak Dave, Hady Ahmady Phoulady, Peter R. Mouton:
Iterative Deep Learning Based Unbiased Stereology With Human-in-the-Loop. CoRR abs/1901.04355 (2019) - 2018
- [j64]Saeed S. Alahmari, Dmitry Cherezov, Dmitry B. Goldgof, Lawrence O. Hall, Robert J. Gillies, Matthew B. Schabath:
Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening. IEEE Access 6: 77796-77806 (2018) - [c122]Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Palak Dave, Hady Ahmady Phoulady, Peter R. Mouton:
Iterative Deep Learning Based Unbiased Stereology with Human-in-the-Loop. ICMLA 2018: 665-670 - [c121]Rahul Paul, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath, Robert J. Gillies:
Predicting Nodule Malignancy using a CNN Ensemble Approach. IJCNN 2018: 1-8 - [c120]Rahul Paul, Ying Liu, Qian Li, Lawrence O. Hall, Dmitry B. Goldgof, Yoganand Balagurunathan, Matthew B. Schabath, Robert J. Gillies:
Representation of Deep Features using Radiologist defined Semantic Features. IJCNN 2018: 1-7 - [c119]Rahul Paul, Muhammad Shafiq-ul-Hassan, Eduardo G. Moros, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Stability of deep features across CT scanners and field of view using a physical phantom. Computer-Aided Diagnosis 2018: 105753P - 2017
- [j63]Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
A framework for nucleus and overlapping cytoplasm segmentation in cervical cytology extended depth of field and volume images. Comput. Medical Imaging Graph. 59: 38-49 (2017) - [j62]Meng Fang, Jie Yin, Lawrence O. Hall, Dacheng Tao:
Active Multitask Learning With Trace Norm Regularization Based on Excess Risk. IEEE Trans. Cybern. 47(11): 3906-3915 (2017) - [c118]Kaoutar Ben Ahmed, Lawrence O. Hall, Dmitry B. Goldgof, Renhao Liu, Robert A. Gatenby:
Fine-tuning convolutional deep features for MRI based brain tumor classification. Computer-Aided Diagnosis 2017: 101342E - [c117]Renhao Liu, Lawrence O. Hall, Kevin W. Bowyer, Dmitry B. Goldgof, Robert A. Gatenby, Kaoutar Ben Ahmed:
Synthetic minority image over-sampling technique: How to improve AUC for glioblastoma patient survival prediction. SMC 2017: 1357-1362 - [c116]Ekambaram Rajmadhan, Dmitry B. Goldgof, Lawrence O. Hall:
Finding label noise examples in large scale datasets. SMC 2017: 2420-2424 - 2016
- [j61]Ekambaram Rajmadhan, Sergiy Fefilatyev, Matthew Shreve, Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Rangachar Kasturi:
Active cleaning of label noise. Pattern Recognit. 51: 463-480 (2016) - [c115]Hady Ahmady Phoulady, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
Automatic quantification and classification of cervical cancer via Adaptive Nucleus Shape Modeling. ICIP 2016: 2658-2662 - [c114]Alireza Chakeri, Hamidreza Farhidzadeh, Lawrence O. Hall:
Spectral sparsification in spectral clustering. ICPR 2016: 2301-2306 - [c113]Renhao Liu, Lawrence O. Hall, Dmitry B. Goldgof, Mu Zhou, Robert A. Gatenby, Kaoutar Ben Ahmed:
Exploring deep features from brain tumor magnetic resonance images via transfer learning. IJCNN 2016: 235-242 - [c112]Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
A new approach to detect and segment overlapping cells in multi-layer cervical cell volume images. ISBI 2016: 201-204 - [c111]Baishali Chaudhury, Mu Zhou, Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Robert J. Weinfurtner, Jennifer S. Drukteinis:
Predicting Ki67% expression from DCE-MR images of breast tumors using textural kinetic features in tumor habitats. Computer-Aided Diagnosis 2016: 97850T - [c110]Hamidreza Farhidzadeh, Baishali Chaudhury, Jacob G. Scott, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan:
Signal intensity analysis of ecological defined habitat in soft tissue sarcomas to predict metastasis development. Computer-Aided Diagnosis 2016: 97851H - [c109]Hamidreza Farhidzadeh, Joo Y. Kim, Jacob G. Scott, Dmitry B. Goldgof, Lawrence O. Hall, Louis B. Harrison:
Classification of progression free survival with nasopharyngeal carcinoma tumors. Computer-Aided Diagnosis 2016: 97851I - [c108]Benjamin Geiger, Samuel H. Hawkins, Lawrence O. Hall, Dmitry B. Goldgof, Yoganand Balagurunathan, Robert A. Gatenby, Robert J. Gillies:
Change descriptors for determining nodule malignancy in national lung screening trial CT screening images. Computer-Aided Diagnosis 2016: 978535 - [c107]Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
Nucleus segmentation in histology images with hierarchical multilevel thresholding. Digital Pathology 2016: 979111 - [c106]Dmitry Cherezov, Samuel H. Hawkins, Dmitry B. Goldgof, Lawrence O. Hall, Yoganand Balagurunathan, Robert J. Gillies, Matthew B. Schabath:
Improving malignancy prediction through feature selection informed by nodule size ranges in NLST. SMC 2016: 1939-1944 - [c105]Rahul Paul, Samuel H. Hawkins, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies:
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT. SMC 2016: 2570-2575 - [c104]Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Jacob G. Scott, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan:
A quantitative histogram-based approach to predict treatment outcome for Soft Tissue Sarcomas using pre- and post-treatment MRIs. SMC 2016: 4549-4554 - 2015
- [c103]Alireza Chakeri, Lawrence O. Hall:
Large Data Clustering Using Quadratic Programming: A Comprehensive Quantitative Analysis. ICDM Workshops 2015: 806-813 - [c102]Hamidreza Farhidzadeh, Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan:
Prediction of treatment outcome in soft tissue sarcoma based on radiologically defined habitats. Computer-Aided Diagnosis 2015: 94141U - [c101]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies, Robert A. Gatenby:
Imbalanced learning for clinical survival group prediction of brain tumor patients. Computer-Aided Diagnosis 2015: 94142K - [c100]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robin Russo, Robert J. Gillies, Robert A. Gatenby:
Decoding brain cancer dynamics: a quantitative histogram-based approach using temporal MRI. Computer-Aided Diagnosis 2015: 94142H - [c99]Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
Identifying metastatic breast tumors using textural kinetic features of a contrast based habitat in DCE-MRI. Computer-Aided Diagnosis 2015: 941415 - [c98]Baishali Chaudhury, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
Correlation Based Random Subspace Ensembles for Predicting Number of Axillary Lymph Node Metastases in Breast DCE-MRI Tumors. SMC 2015: 2164-2169 - [c97]Hailing Zhou, Dmitry B. Goldgof, Samuel H. Hawkins, Lei Wei, Ying Liu, Douglas C. Creighton, Robert J. Gillies, Lawrence O. Hall, Saeid Nahavandi:
A Robust Approach for Automated Lung Segmentation in Thoracic CT. SMC 2015: 2267-2272 - [c96]Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan:
Texture Feature Analysis to Predict Metastatic and Necrotic Soft Tissue Sarcomas. SMC 2015: 2798-2802 - 2014
- [j60]Samuel H. Hawkins, John N. Korecki, Yoganand Balagurunathan, Yuhua Gu, Virendra Kumar, Satrajit Basu, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies:
Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features. IEEE Access 2: 1418-1426 (2014) - [j59]Yoganand Balagurunathan, Virendra Kumar, Yuhua Gu, Jongphil Kim, Hua Wang, Ying Liu, Dmitry B. Goldgof, Lawrence O. Hall, René Korn, Binsheng Zhao, Lawrence H. Schwartz, Satrajit Basu, Steven Eschrich, Robert A. Gatenby, Robert J. Gillies:
Test-Retest Reproducibility Analysis of Lung CT Image Features. J. Digit. Imaging 27(6): 805-823 (2014) - [j58]Jonathon K. Parker, Lawrence O. Hall:
Accelerating Fuzzy-C Means Using an Estimated Subsample Size. IEEE Trans. Fuzzy Syst. 22(5): 1229-1244 (2014) - [c95]Lawrence O. Hall, Alireza Chakeri:
Relational data partitioning using evolutionary game theory. CIDM 2014: 113-120 - [c94]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof:
Exploring Brain Tumor Heterogeneity for Survival Time Prediction. ICPR 2014: 580-585 - [c93]Alireza Chakeri, Lawrence O. Hall:
Dominant Sets as a Framework for Cluster Ensembles: An Evolutionary Game Theory Approach. ICPR 2014: 3457-3462 - [c92]Baishali Chaudhury, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis. Computer-Aided Diagnosis 2014: 90351V - [c91]Hamidreza Farhidzadeh, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Meera Raghavan, Robert A. Gatenby:
Prediction of treatment response and metastatic disease in soft tissue sarcoma. Computer-Aided Diagnosis 2014: 903518 - [c90]Hady Ahmady Phoulady, Baishali Chaudhury, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton, Ardeshir Hakam, Erin M. Siegel:
Experiments with large ensembles for segmentation and classification of cervical cancer biopsy images. SMC 2014: 870-875 - [c89]Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
Using features from tumor subregions of breast DCE-MRI for estrogen receptor status prediction. SMC 2014: 2624-2629 - 2013
- [j57]Yuhua Gu, Virendra Kumar, Lawrence O. Hall, Dmitry B. Goldgof, Ching-Yen Li, René Korn, Claus Bendtsen, Emmanuel Rios Velazquez, Andre Dekker, Hugo J. W. L. Aerts, Philippe Lambin, Xiuli Li, Jie Tian, Robert A. Gatenby, Robert J. Gillies:
Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach. Pattern Recognit. 46(3): 692-702 (2013) - [c88]Alireza Chakeri, Iman Nekooeimehr, Lawrence O. Hall:
Dempster-Shafer theory of evidence in Single Pass Fuzzy C Means. FUZZ-IEEE 2013: 1-5 - [c87]Baishali Chaudhury, Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton, Ardeshir Hakam, Erin M. Siegel:
An Ensemble Algorithm Framework for Automated Stereology of Cervical Cancer. ICIAP (1) 2013: 823-832 - [c86]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies, Robert A. Gatenby:
Survival time prediction of patients with glioblastoma multiforme tumors using spatial distance measurement. Computer-Aided Diagnosis 2013: 86702O - [c85]Henry Krewer, Benjamin Geiger, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Melvyn Tockman, Robert J. Gillies:
Effect of Texture Features in Computer Aided Diagnosis of Pulmonary Nodules in Low-Dose Computed Tomography. SMC 2013: 3887-3891 - [c84]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies:
A Texture Feature Ranking Model for Predicting Survival Time of Brain Tumor Patients. SMC 2013: 4533-4538 - 2012
- [j56]Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, John N. Korecki, Steven Eschrich:
Iterative Feature perturbation as a gene Selector for microarray Data. Int. J. Pattern Recognit. Artif. Intell. 26(5) (2012) - [j55]Timothy C. Havens, James C. Bezdek, Christopher Leckie, Lawrence O. Hall, Marimuthu Palaniswami:
Fuzzy c-Means Algorithms for Very Large Data. IEEE Trans. Fuzzy Syst. 20(6): 1130-1146 (2012) - [j54]Lawrence O. Hall:
Objective function-based clustering. WIREs Data Mining Knowl. Discov. 2(4): 326-339 (2012) - [c83]Baishali Chaudhury, Kurt Kramer, Daniel Elozory, Gerry Hernandez, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
A novel algorithm for automated counting of stained cells on thick tissue sections. CBMS 2012: 1-6 - [c82]Jonathon K. Parker, Lawrence O. Hall, James C. Bezdek:
Comparison of scalable fuzzy clustering methods. FUZZ-IEEE 2012: 1-9 - [c81]Sergiy Fefilatyev, Matthew Shreve, Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Rangachar Kasturi, Kendra Daly, Andrew Remsen, Horst Bunke:
Label-noise reduction with support vector machines. ICPR 2012: 3504-3508 - [c80]Lawrence O. Hall:
Exploring Big Data with Scalable Soft Clustering. SMPS 2012: 11-15 - 2011
- [j53]Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
Detecting and ordering salient regions. Data Min. Knowl. Discov. 22(1-2): 259-290 (2011) - [j52]Lawrence O. Hall, Dmitry B. Goldgof:
Convergence of the Single-Pass and Online Fuzzy C-Means Algorithms. IEEE Trans. Fuzzy Syst. 19(4): 792-794 (2011) - [c79]Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Andrew Remsen:
Increased classification accuracy and speedup through pair-wise feature selection for support vector machines. CIDM 2011: 318-324 - [c78]Sergiy Fefilatyev, Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Rangachar Kasturi, Andrew Remsen, Kendra Daly:
Detection of Anomalous Particles from the Deepwater Horizon Oil Spill Using the SIPPER3 Underwater Imaging Platform. ICDM Workshops 2011: 741-748 - [c77]Larry Shoemaker, Lawrence O. Hall:
Anomaly Detection Using Ensembles. MCS 2011: 6-15 - [c76]Om Pavithra Bonam, Daniel Elozory, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Osvaldo Mangual, Peter R. Mouton:
Toward automated quantification of biological microstructures using unbiased stereology. Computer-Aided Diagnosis 2011: 79633G - [c75]Daniel T. Elozory, Om Pavithra Bonam, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Osvaldo Mangual, Peter R. Mouton:
Automatic location of microscopic focal planes for computerized stereology. Computer-Aided Diagnosis 2011: 79633C - [c74]John N. Korecki, Lawrence O. Hall, Dmitry B. Goldgof, Steven Eschrich:
Procedure for stability analysis of gene selection from cross-site gene expression data. SMC 2011: 909-913 - [c73]Satrajit Basu, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Virendra Kumar, Jung Choi, Robert J. Gillies, Robert A. Gatenby:
Developing a classifier model for lung tumors in CT-scan images. SMC 2011: 1306-1312 - [i2]Kevin W. Bowyer, Nitesh V. Chawla, Lawrence O. Hall, W. Philip Kegelmeyer:
SMOTE: Synthetic Minority Over-sampling Technique. CoRR abs/1106.1813 (2011) - 2010
- [c72]Lawrence O. Hall, Dmitry B. Goldgof:
On convergence properties of the singlepass and online fuzzy c-means algorithm. FUZZ-IEEE 2010: 1-3 - [c71]Jonathon K. Parker, Lawrence O. Hall, Abraham Kandel:
Scalable fuzzy neighborhood DBSCAN. FUZZ-IEEE 2010: 1-8 - [c70]Yuhua Gu, Lawrence O. Hall, Dmitry B. Goldgof:
Evaluating scalable fuzzy clustering. SMC 2010: 873-880 - [c69]Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, Steven Eschrich:
Filtering for improved gene selection on microarray data. SMC 2010: 3250-3257
2000 – 2009
- 2009
- [j51]Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof:
A scalable framework for cluster ensembles. Pattern Recognit. 42(5): 676-688 (2009) - [j50]Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Andrew Remsen, Tong Luo:
Fast Support Vector Machines for Continuous Data. IEEE Trans. Syst. Man Cybern. Part B 39(4): 989-1001 (2009) - [j49]Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Andrew Maudsley, Ammar Darkazanli:
A Scalable Framework For Segmenting Magnetic Resonance Images. J. Signal Process. Syst. 54(1-3): 183-203 (2009) - [c68]Yuhua Gu, Lawrence O. Hall, Dmitry B. Goldgof:
Ant Clustering Using Ensembles of Partitions. MCS 2009: 283-292 - [c67]Weijian Cheng, Lawrence O. Hall, Dmitry B. Goldgof, Chuanmin Hu, Inia M. Soto:
Automatic Red Tide Detection from MODIS Satellite Images. SMC 2009: 1864-1868 - [p1]Lawrence O. Hall, Dmitry B. Goldgof, Juana Canul-Reich, Prodip Hore, Weijian Cheng, Larry Shoemaker:
Scaling Fuzzy Models. Scalable Fuzzy Algorithms for Data Management and Analysis 2009: 31-53 - 2008
- [j48]Nitesh V. Chawla, David A. Cieslak, Lawrence O. Hall, Ajay Joshi:
Automatically countering imbalance and its empirical relationship to cost. Data Min. Knowl. Discov. 17(2): 225-252 (2008) - [j47]Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
Using classifier ensembles to label spatially disjoint data. Inf. Fusion 9(1): 120-133 (2008) - [c66]John Nicholas Korecki, Robert E. Banfield, Larry O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
Semi-supervised learning on large complex simulations. ICPR 2008: 1-4 - [c65]Larry Shoemaker, Robert E. Banfield, Larry O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
Detecting and ordering salient regions for efficient browsing. ICPR 2008: 1-4 - [c64]Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, Steven Eschrich:
Feature selection for microarray data by AUC analysis. SMC 2008: 768-773 - 2007
- [j46]Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
A Comparison of Decision Tree Ensemble Creation Techniques. IEEE Trans. Pattern Anal. Mach. Intell. 29(1): 173-180 (2007) - [j45]Parag M. Kanade, Lawrence O. Hall:
Fuzzy Ants and Clustering. IEEE Trans. Syst. Man Cybern. Part A 37(5): 758-769 (2007) - [c63]Vidya P. Kamath, Lawrence O. Hall, Timothy Yeatman, Steven Eschrich:
Multivariate Feature Selection using Random Subspace Classifiers for Gene Expression Data. BIBE 2007: 1041-1045 - [c62]Juana Canul-Reich, Larry Shoemaker, Lawrence O. Hall:
Ensembles of Fuzzy Classifiers. FUZZ-IEEE 2007: 1-6 - [c61]Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof:
Single Pass Fuzzy C Means. FUZZ-IEEE 2007: 1-7 - [c60]Li Chen, Dmitry B. Goldgof, Lawrence O. Hall, Steven Eschrich:
Noise-Based Feature Perturbation as a Selection Method for Microarray Data. ISBRA 2007: 237-247 - [c59]Lawrence O. Hall, Robert E. Banfield, Kevin W. Bowyer, W. Philip Kegelmeyer:
Boosting Lite - Handling Larger Datasets and Slower Base Classifiers. MCS 2007: 161-170 - [c58]Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof:
A fuzzy c means variant for clustering evolving data streams. SMC 2007: 360-365 - [c57]Sergiy Fefilatyev, Tim V. Ivanovskiy, Lawrence O. Hall, Dmitry B. Goldgof, Shibendra S. Pobi, Halina Greenstien, Amit P. Pathak, Christopher R. Garret:
Clinical deployment of a medical expert system to increase accruals for clinical trials: Challenges. SMC 2007: 1482-1487 - 2006
- [j44]Yong Zhang, Lawrence O. Hall, Dmitry B. Goldgof, Sudeep Sarkar:
A constrained genetic approach for computing material property of elastic objects. IEEE Trans. Evol. Comput. 10(3): 341-357 (2006) - [c56]Yuhua Gu, Lawrence O. Hall:
Kernel Based Fuzzy Ant Clustering with Partition Validity. FUZZ-IEEE 2006: 61-65 - [c55]Sergiy Fefilatyev, Volha Smarodzinava, Lawrence O. Hall, Dmitry B. Goldgof:
Horizon Detection Using Machine Learning Techniques. ICMLA 2006: 17-21 - [c54]Cindy L. Bethel, Lawrence O. Hall, Dmitry B. Goldgof:
Mining for Implications in Medical Data. ICPR (1) 2006: 1212-1215 - [c53]Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
Learning to Predict Salient Regions from Disjoint and Skewed Training Sets. ICTAI 2006: 116-126 - [c52]Shibendra S. Pobi, Lawrence O. Hall:
Predicting Juvenile Diabetes from Clinical Test Results. IJCNN 2006: 2159-2165 - [c51]Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof:
A Cluster Ensemble Framework for Large Data sets. SMC 2006: 3342-3347 - 2005
- [j43]Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
Ensemble diversity measures and their application to thinning. Inf. Fusion 6(1): 49-62 (2005) - [j42]Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins:
Active Learning to Recognize Multiple Types of Plankton. J. Mach. Learn. Res. 6: 589-613 (2005) - [c50]Lawrence O. Hall, Parag M. Kanade:
Swarm Based Fuzzy Clustering with Partition Validity. FUZZ-IEEE 2005: 991-995 - [c49]Lawrence O. Hall, Parag M. Kanade:
Scalable Swarm Based Fuzzy Clustering. GfKl 2005: 21-31 - [c48]Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, Andrew Remsen:
Bit Reduction Support Vector Machine. ICDM 2005: 733-736 - [c47]Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
Ensembles of Classifiers from Spatially Disjoint Data. Multiple Classifier Systems 2005: 196-205 - [c46]Yuhua Gu, Lawrence O. Hall, Dmitry B. Goldgof, Parag M. Kanade, F. Reed Murtagh:
Sequence tolerant segmentation system of brain MRI. SMC 2005: 2936-2943 - 2004
- [j41]Eugene Fink, Princeton K. Kokku, Savvas Nikiforou, Lawrence O. Hall, Dmitry B. Goldgof, Jeffrey P. Krischer:
Selection of patients for clinical trials: an interactive web-based system. Artif. Intell. Medicine 31(3): 241-254 (2004) - [j40]Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
Learning Ensembles from Bites: A Scalable and Accurate Approach. J. Mach. Learn. Res. 5: 421-451 (2004) - [j39]Xiaomei Liu, Lawrence O. Hall, Kevin W. Bowyer:
Comments on "A Parallel Mixture of SVMs for Very Large Scale Problems". Neural Comput. 16(7): 1345-1351 (2004) - [j38]Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins:
Recognizing plankton images from the shadow image particle profiling evaluation recorder. IEEE Trans. Syst. Man Cybern. Part B 34(4): 1753-1762 (2004) - [j37]Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins:
Errata to "Recognizing Plankton Images From the Shadow Image Particle Profiling Evaluation Recorder". IEEE Trans. Syst. Man Cybern. Part B 34(6): 2423-2423 (2004) - [j36]Lawrence O. Hall:
List of Reviewers. IEEE Trans. Syst. Man Cybern. Part B 34(6): 2486-2491 (2004) - [c45]Bhavesh D. Goswami, Lawrence O. Hall, Dmitry B. Goldgof, Eugene Fink, Jeffrey P. Krischer:
Using Probabilistic Methods to Optimize Data Entry in Accrual of Patients to Clinical Trials. CBMS 2004: 434- - [c44]Prodip Hore, Lawrence O. Hall:
Scalable clustering: a distributed approach. FUZZ-IEEE 2004: 143-148 - [c43]Parag M. Kanade, Lawrence O. Hall:
Fuzzy ant clustering by centroid positioning. FUZZ-IEEE 2004: 371-376 - [c42]Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins:
Active Learning to Recognize Multiple Types of Plankton. ICPR (3) 2004: 478-481 - [c41]Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, Divya Bhadoria, W. Philip Kegelmeyer, Steven Eschrich:
A Comparison of Ensemble Creation Techniques. Multiple Classifier Systems 2004: 223-232 - [c40]Lawrence O. Hall, Divya Bhadoria, Kevin W. Bowyer:
Learning a model from spatially disjoint data. SMC (2) 2004: 1447-1451 - [c39]Xiaomei Liu, Kevin W. Bowyer, Lawrence O. Hall:
Decision trees work better than feed-forward back-prop neural nets for a specific class of problems. SMC (6) 2004: 5969-5974 - 2003
- [j35]Lawrence O. Hall, Kevin W. Bowyer, Robert E. Banfield, Steven Eschrich, Richard Collins:
Is Error-Based Pruning Redeemable? Int. J. Artif. Intell. Tools 12(3): 249-264 (2003) - [j34]Nitesh V. Chawla, Thomas E. Moore, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer, Clayton Springer:
Distributed learning with bagging-like performance. Pattern Recognit. Lett. 24(1-3): 455-471 (2003) - [j33]Steven Eschrich, Jingwei Ke, Lawrence O. Hall, Dmitry B. Goldgof:
Fast accurate fuzzy clustering through data reduction. IEEE Trans. Fuzzy Syst. 11(2): 262-270 (2003) - [j32]Michael R. Berthold, Lawrence O. Hall:
Visualizing fuzzy points in parallel coordinates. IEEE Trans. Fuzzy Syst. 11(3): 369-374 (2003) - [c38]Steven Eschrich, Lawrence O. Hall:
Learning from soft partitions of data: reducing the variance. FUZZ-IEEE 2003: 666-671 - [c37]Lawrence O. Hall, Kevin W. Bowyer, Robert E. Banfield, Divya Bhadoria, W. Philip Kegelmeyer, Steven Eschrich:
Comparing Pure Parallel Ensemble Creation Techniques Against Bagging. ICDM 2003: 533-536 - [c36]Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
A New Ensemble Diversity Measure Applied to Thinning Ensembles. Multiple Classifier Systems 2003: 306-316 - [c35]Nitesh V. Chawla, Aleksandar Lazarevic, Lawrence O. Hall, Kevin W. Bowyer:
SMOTEBoost: Improving Prediction of the Minority Class in Boosting. PKDD 2003: 107-119 - [c34]Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins:
Learning to recognize plankton. SMC 2003: 888-893 - [c33]Lawrence O. Hall, Xiaomei Liu, Kevin W. Bowyer, Robert E. Banfield:
Why are neural networks sometimes much more accurate than decision trees: an analysis on a bio-informatics problem. SMC 2003: 2851-2856 - [c32]Eugene Fink, Lawrence O. Hall, Dmitry B. Goldgof, Bhavesh D. Goswami, Matthew Boonstra, Jeffrey P. Krischer:
Experiments on the automated selection of patients for clinical trials. SMC 2003: 4541-4545 - 2002
- [j31]Nitesh V. Chawla, Kevin W. Bowyer, Lawrence O. Hall, W. Philip Kegelmeyer:
SMOTE: Synthetic Minority Over-sampling Technique. J. Artif. Intell. Res. 16: 321-357 (2002) - [j30]Mingrui Zhang, Lawrence O. Hall, Dmitry B. Goldgof:
A generic knowledge-guided image segmentation and labeling system using fuzzy clustering algorithms. IEEE Trans. Syst. Man Cybern. Part B 32(5): 571-582 (2002) - [c31]Yong Zhang, Lawrence O. Hall, Dmitry B. Goldgof, Sudeep Sarkar:
A constrained genetic approach for reconstructing Young's modulus of elastic objects from boundary displacement measurements. IEEE Congress on Evolutionary Computation 2002: 1003-1008 - [c30]Girish Keswani, Lawrence O. Hall:
Text classification with enhanced semi-supervised fuzzy clustering. FUZZ-IEEE 2002: 621-626 - [c29]Lawrence O. Hall, Richard Collins, Kevin W. Bowyer, Robert E. Banfield:
Error-Based Pruning of Decision Trees Grown on Very Large Data Sets Can Work! ICTAI 2002: 233-238 - [c28]Steven Eschrich, Nitesh V. Chawla, Lawrence O. Hall:
Generalization Methods in Bioinformatics. BIOKDD 2002: 25-32 - [c27]Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, Thomas E. Moore, W. Philip Kegelmeyer:
Distributed Pasting of Small Votes. Multiple Classifier Systems 2002: 52-61 - 2001
- [j29]Lynn M. Fletcher-Heath, Lawrence O. Hall, Dmitry B. Goldgof, F. Reed Murtagh:
Automatic segmentation of non-enhancing brain tumors in magnetic resonance images. Artif. Intell. Medicine 21(1-3): 43-63 (2001) - [j28]Horia-Nicolai L. Teodorescu, Abraham Kandel, Lawrence O. Hall:
Report of research activities in fuzzy AI and medicine at USF CSE. Artif. Intell. Medicine 21(1-3): 177-183 (2001) - [j27]Kevin W. Bowyer, Lawrence O. Hall:
Reducing Effects of Plagiarism in Programming Classes. J. Inf. Syst. Educ. 12(3): 141-148 (2001) - [j26]Lawrence O. Hall:
Rule chaining in fuzzy expert systems. IEEE Trans. Fuzzy Syst. 9(6): 822-828 (2001) - [j25]K. Patipati, Lawrence O. Hall:
SMCB goes all electronic. IEEE Trans. Syst. Man Cybern. Part B 31(4): 481 (2001) - [c26]Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer:
Bagging Is a Small-Data-Set Phenomenon. CVPR (2) 2001: II:684-689 - [c25]T. Perroud, Karin Sobottka, Horst Bunke, Lawrence O. Hall:
Text Extraction from Color Documents - Clustering Approaches in Three and Four Dimensions. ICDAR 2001: 937-941 - [c24]Nitesh V. Chawla, Steven Eschrich, Lawrence O. Hall:
Creating Ensembles of Classifiers. ICDM 2001: 580-581 - [c23]Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer:
Investigation of bagging-like effects and decision trees versus neural nets in protein secondary structure prediction. BIOKDD 2001: 50-59 - [c22]Lawrence O. Hall:
Data mining from extreme data sets: very large and/or very skewed data sets. SMC 2001: 2555 - 2000
- [j24]Mingrui Zhang, Lawrence O. Hall, Dmitry B. Goldgof, Frank E. Müller-Karger:
Knowledge-Guided Classification of Coastal Zone Color Images Off the West Florida Shelf. Int. J. Pattern Recognit. Artif. Intell. 14(8): 987-1007 (2000) - [c21]Lawrence O. Hall:
Chaining in fuzzy rule-based systems. FUZZ-IEEE 2000: 906-910 - [c20]Wensheng Yao, Lawrence O. Hall, Dmitry B. Goldgof, Frank E. Müller-Karger:
Finding Green River in SeaWiFS Satellite Images. ICPR 2000: 2307-2310 - [c19]Kevin W. Bowyer, Lawrence O. Hall, Thomas Moore, Nitesh V. Chawla, W. Philip Kegelmeyer:
A parallel decision tree builder for mining very large visualization datasets. SMC 2000: 1888-1893
1990 – 1999
- 1999
- [j23]Lawrence O. Hall, Ibrahim Burak Özyurt, James C. Bezdek:
Clustering with a genetically optimized approach. IEEE Trans. Evol. Comput. 3(2): 103-112 (1999) - [j22]Ibrahim Burak Özyurt, Lawrence O. Hall, Aydin K. Sunol:
SQFDiag: semi-quantitative model-based fault monitoring and diagnosis via episodic fuzzy rules. IEEE Trans. Syst. Man Cybern. Part A 29(3): 294-306 (1999) - [c18]Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowyer, W. Philip Kegelmeyer:
Learning Rules from Distributed Data. Large-Scale Parallel Data Mining 1999: 211-220 - 1998
- [j21]Tai Wai Cheng, Dmitry B. Goldgof, Lawrence O. Hall:
Fast fuzzy clustering. Fuzzy Sets Syst. 93(1): 49-56 (1998) - [j20]Lawrence O. Hall, Petter Lande:
Generation of Fuzzy Rules from Decision Trees. J. Adv. Comput. Intell. Intell. Informatics 2(4): 128-133 (1998) - [j19]Matthew C. Clark, Lawrence O. Hall, Dmitry B. Goldgof, Robert P. Velthuizen, F. Reed Murtagh, Martin L. Silbiger:
Automatic Tumor Segmentation Using Knowledge-Based Clustering. IEEE Trans. Medical Imaging 17(2): 187-201 (1998) - [c17]Sanjukta Bhanja, Lynn M. Fletcher-Heath, Lawrence O. Hall, Dmitry B. Goldgof, Jeffrey P. Krischer:
A Qualitative Expert System for Clinical Trial Assignment. FLAIRS 1998: 84-88 - [c16]Ibrahim Burak Özyurt, Aydin K. Sunol, Lawrence O. Hall:
Chemical Process Fault Diagnosis Using Kernel Retrofitted Fuzzy Genetic Algorithm Based Learner (FGAL) with a Hidden Markov Model. IEA/AIE (Vol. 1) 1998: 190-199 - [c15]Matthew C. Clark, Lawrence O. Hall, Dmitry B. Goldgof, Robert Paul Velthuizen, F. Reed Murtagh, Martin L. Silbiger:
Automatic brain tumor segmentation. Image Processing 1998 - [c14]Lynn M. Fletcher-Heath, Lawrence O. Hall, Dmitry B. Goldgof:
Segmenting nonenhancing brain tumors from normal tissues in magnetic resonance images. Image Processing 1998 - [c13]Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowyer:
Decision tree learning on very large data sets. SMC 1998: 2579-2584 - 1997
- [j18]Lawrence O. Hall:
Confirmation and denial as plausible modes of fuzzy inference. Fuzzy Sets Syst. 86(3): 307-309 (1997) - [j17]Robert P. Velthuizen, Lawrence O. Hall, Laurence P. Clarke, Martin L. Silbiger:
An investigation of mountain method clustering for large data sets. Pattern Recognit. 30(7): 1121-1135 (1997) - [c12]Jie Lei, Lawrence O. Hall:
Speaker recognition with a self-configuring neural network. ICNN 1997: 2351-2354 - 1996
- [j16]Katsuaki Sanou, Steve G. Romaniuk, Lawrence O. Hall:
Encoding of Production Rules in a Connectionist Network. J. Intell. Fuzzy Syst. 4(1): 1-18 (1996) - [j15]Amine Bensaid, Lawrence O. Hall, James C. Bezdek, Laurence P. Clarke:
Partially supervised clustering for image segmentation. Pattern Recognit. 29(5): 859-871 (1996) - [j14]Lawrence O. Hall, Richard J. Hathaway:
Fuzzy Systems Toolbox, Fuzzy Logic Toolbox [Software Review]. IEEE Trans. Fuzzy Syst. 4(1): 82 (1996) - [j13]Amine Bensaid, Lawrence O. Hall, James C. Bezdek, Laurence P. Clarke, Martin L. Silbiger, John A. Arrington, F. Reed Murtagh:
Validity-guided (re)clustering with applications to image segmentation. IEEE Trans. Fuzzy Syst. 4(2): 112-123 (1996) - [c11]Mingrui Zhang, Lawrence O. Hall, Dmitry B. Goldgof:
Knowledge-based classification of CZCS images and monitoring of red tides off the west Florida shelf. ICPR 1996: 452-456 - [c10]Robert Paul Velthuizen, Lawrence O. Hall, Laurence P. Clarke:
Novel approach to feature extraction for MRI segmentation. Image Processing 1996 - 1995
- [j12]Kevin S. Woods, Diane J. Cook, Lawrence O. Hall, Kevin W. Bowyer, Louise Stark:
Learning Membership Functions in a Function-Based Object Recognition System. J. Artif. Intell. Res. 3: 187-222 (1995) - [c9]Matthew C. Clark, Lawrence O. Hall, Dmitry B. Goldgof, Martin L. Silbiger:
Using Fuzzy Information in Knowledge Guided Segmentation of Brain Tumors. Fuzzy Logic in Artificial Intelligence 1995: 167-181 - [i1]Kevin S. Woods, Diane J. Cook, Lawrence O. Hall, Kevin W. Bowyer, Louise Stark:
Learning Membership Functions in a Function-Based Object Recognition System. CoRR abs/cs/9510103 (1995) - 1994
- [c8]James C. Bezdek, Srinivas Boggavarapu, Lawrence O. Hall, Amine Bensaid:
Genetic Algorithm Guided Clustering. International Conference on Evolutionary Computation 1994: 34-39 - [c7]Matthew C. Clark, Lawrence O. Hall, Chunlin Li, Dmitry B. Goldgof:
Knowledge based (re-)clustering. ICPR (2) 1994: 245-250 - 1993
- [j11]Diane J. Cook, Lawrence O. Hall, Willard Thomas:
Parallel search using transformation-ordering Lterative-Deepening-A. Int. J. Intell. Syst. 8(8): 855-873 (1993) - [j10]Louise Stark, Lawrence O. Hall, Kevin W. Bowyer:
Methods for Combination of Evidence in Function-Based 3-D Object Recognition. Int. J. Pattern Recognit. Artif. Intell. 7(3): 573-594 (1993) - [j9]Steve G. Romaniuk, Lawrence O. Hall:
SC-net: A hybrid connectionist, symbolic system. Inf. Sci. 71(3): 223-268 (1993) - [j8]Steve G. Romaniuk, Lawrence O. Hall:
Divide and Conquer Neural Networks. Neural Networks 6(8): 1105-1116 (1993) - [j7]Chunlin Li, Dmitry B. Goldgof, Lawrence O. Hall:
Knowledge-based classification and tissue labeling of MR images of human brain. IEEE Trans. Medical Imaging 12(4): 740-750 (1993) - [c6]Kevin S. Woods, Diane J. Cook, Lawrence O. Hall, Louise Stark, Kevin W. Bowyer:
Learning Fuzzy Membership Functions in a Function-Based Object Recognition System. Fuzzy Logic in Artificial Intelligence 1993: 77-96 - 1992
- [j6]Lawrence O. Hall:
Experimental results from parallel backward-chained expert systems. Int. J. Intell. Syst. 7(6): 505-512 (1992) - [j5]Lawrence O. Hall:
Backpac: A parallel goal-driven reasoning system. Inf. Sci. 62(1-2): 169-182 (1992) - [j4]Lawrence O. Hall, Amine Bensaid, Laurence P. Clarke, Robert P. Velthuizen, Martin L. Silbiger, James C. Bezdek:
A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain. IEEE Trans. Neural Networks 3(5): 672-682 (1992) - [c5]Katsuaki Sanou, Steve G. Romaniuk, Lawrence O. Hall:
A Hybrid/Symbolic Connectionist Production System. ICTAI 1992: 44-53 - 1990
- [c4]Lawrence O. Hall, Steve G. Romaniuk:
A Hybrid Connectionist, Symbolic Learning System. AAAI 1990: 783-788
1980 – 1989
- 1988
- [j3]Lawrence O. Hall:
On the choice of ply operators for modus ponens generation in fuzzy intelligent systems. Int. J. Approx. Reason. 2(2): 101 (1988) - [j2]Lawrence O. Hall, Menahem Friedman, Abraham Kandel:
On the validation and testing of fuzzy expert systems. IEEE Trans. Syst. Man Cybern. 18(6): 1023-1027 (1988) - 1986
- [b1]Lawrence O'Higgins Hall:
A Methodological Approach to a Re-Usable fuzzy Expert System. Florida State University, Tallahassee, USA, 1986 - [j1]Lawrence O. Hall, Sue Szabo, Abraham Kandel:
On the derivation of memberships for fuzzy sets in expert systems. Inf. Sci. 40(1): 39-52 (1986) - [c3]Lawrence O. Hall, Wyllis Bandler, Abraham Kandel:
New Concepts for Expert Systems Capable of Intelligence in an Imprecise Environment. IAS 1986: 246-250 - [c2]Lawrence O. Hall, Abraham Kandel:
Languages for expert system building: a comparison. SIGSMALL 1986: 157-160 - 1985
- [c1]Lawrence O. Hall, Wyllis Bandler:
Relational Knowledge Acquisition. CAIA 1985: 509-513
Coauthor Index
[j75] [c142] [i12] [c141] [j74] [j72] [c140] [c139] [i10] [i9] [c138] [c137] [c136] [j69] [j68] [c133] [c132] [d1] [j67] [c131] [i6] [j66] [j65] [c129] [i4] [c127] [c126] [c125] [i3] [j64] [c122] [c121] [c120] [c119] [j63] [c118] [c117] [c116] [j61] [c115] [c113] [c112] [c111] [c110] [c109] [c108] [c107] [c106] [c105] [c104] [c102] [c101] [c100] [c99] [c98] [c97] [c96] [j60] [j59] [c94] [c92] [c91] [c90] [c89] [j57] [c87] [c86] [c85] [c84] [j56] [c83] [c81] [j52] [c79] [c78] [c76] [c75] [c74] [c73] [c72] [c70] [c69] [j51] [j50] [j49] [c68] [c67] [p1] [c64] [c61] [c60] [c58] [c57] [j44] [c55] [c54] [c51] [j42] [c48] [c46] [j41] [j38] [j37] [c45] [c42] [j33] [c34] [c32] [j30] [c31] [j29] [j24] [c20] [j21] [j19] [c17] [c15] [c14] [c11] [c9] [c7] [j7]
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