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ORCIDMahesan Niranjan
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- affiliation: University of Southampton, UK
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2020 – today
- 2024
[j68]Ioan Ieremie
, Rob M. Ewing, Mahesan Niranjan:
Protein language models meet reduced amino acid alphabets. Bioinform. 40(2) (2024)- [j67]Keqiang Fan, Xiaohao Cai, Mahesan Niranjan:
Discrepancy-based diffusion models for lesion detection in brain MRI. Comput. Biol. Medicine 181: 109079 (2024) - [j66]Keqiang Fan, Xiaohao Cai, Mahesan Niranjan:
Non-negative subspace feature representation for few-shot learning in medical imaging. Image Vis. Comput. 152: 105334 (2024) - [j65]Andrei C. Rusu, Katayoun Farrahi, Mahesan Niranjan:
EpiCURB: Learning to Derive Epidemic Control Policies. IEEE Pervasive Comput. 23(1): 57-62 (2024) - [c77]Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim:
SliceFormer: Deep Dense Depth Estimation from a Single Indoor Omnidirectional Image Using a Slice-Based Transformer. ICEIC 2024: 1-4 - [c76]Junyu Mao, Stuart E. Middleton, Mahesan Niranjan:
Do Prompt Positions Really Matter? NAACL-HLT (Findings) 2024: 4102-4130 - [i16]Keqiang Fan, Xiaohao Cai, Mahesan Niranjan:
Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imaging. CoRR abs/2404.02656 (2024) - [i15]Keqiang Fan, Xiaohao Cai, Mahesan Niranjan:
Discrepancy-based Diffusion Models for Lesion Detection in Brain MRI. CoRR abs/2405.04974 (2024) - [i14]Mona Alawadh, Mahesan Niranjan, Hansung Kim:
Semantic Scene Completion with Multi-Feature Data Balancing Network. CoRR abs/2412.01431 (2024) - 2023
- [j64]Michal Kubacki, Mahesan Niranjan:
Quantum annealing-based clustering of single cell RNA-seq data. Briefings Bioinform. 24(6) (2023) - [j63]Alex Thomas, Mahesan Niranjan, Julian Legg:
Causal Analysis of Physiological Sleep Data Using Granger Causality and Score-Based Structure Learning. Sensors 23(23): 9455 (2023) - [c75]Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim:
Depth Estimation for a Single Omnidirectional Image with Reversed-Gradient Warming-up Thresholds Discriminator. ICASSP 2023: 1-5 - [c74]Keqiang Fan, Xiaohao Cai, Mahesan Niranjan:
IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer. ICONIP (6) 2023: 57-71 - [i13]Junyu Mao, Stuart E. Middleton, Mahesan Niranjan:
Prompt position really matters in few-shot and zero-shot NLU tasks. CoRR abs/2305.14493 (2023) - [i12]Jiahui Liu, Xiaohao Cai, Mahesan Niranjan:
GO-LDA: Generalised Optimal Linear Discriminant Analysis. CoRR abs/2305.14568 (2023) - [i11]Jiahui Liu, Keqiang Fan, Xiaohao Cai, Mahesan Niranjan:
Few-shot Learning for Inference in Medical Imaging with Subspace Feature Representations. CoRR abs/2306.11152 (2023) - [i10]Keqiang Fan, Xiaohao Cai, Mahesan Niranjan:
IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer. CoRR abs/2308.05633 (2023) - [i9]Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim:
Depth Insight - Contribution of Different Features to Indoor Single-image Depth Estimation. CoRR abs/2311.10042 (2023) - [i8]Jiahui Liu, Xiaohao Cai, Mahesan Niranjan:
Thinking Outside the Box: Orthogonal Approach to Equalizing Protected Attributes. CoRR abs/2311.14733 (2023) - 2022
- [j62]Ioan Ieremie, Rob M. Ewing, Mahesan Niranjan:
TransformerGO: predicting protein-protein interactions by modelling the attention between sets of gene ontology terms. Bioinform. 38(8): 2269-2277 (2022) - [j61]Rubaiyat Mohammad Khondaker, Stephen Gow, Samantha Kanza, Jeremy G. Frey, Mahesan Niranjan:
Robustness under parameter and problem domain alterations of Bayesian optimization methods for chemical reactions. J. Cheminformatics 14(1): 59 (2022) - [j60]Omar Shetta, Mahesan Niranjan, Srinandan Dasmahapatra:
Convex Multi-View Clustering Via Robust Low Rank Approximation With Application to Multi-Omic Data. IEEE ACM Trans. Comput. Biol. Bioinform. 19(6): 3340-3352 (2022) - [c73]Mona Alawadh, Yihong Wu, Yuwen Heng, Luca Remaggi, Mahesan Niranjan, Hansung Kim:
Room Acoustic Properties Estimation from a Single 360° Photo. EUSIPCO 2022: 857-861 - [c72]Shengyu Lu, Sasan Mahmoodi, Mahesan Niranjan:
Robust 3D rotation invariant local binary pattern for volumetric texture classification. ICPR 2022: 578-584 - [c71]Junwen Wang, Xin Du, Katayoun Farrahi, Mahesan Niranjan:
Deep Cascade Learning for Optimal Medical Image Feature Representation. MLHC 2022: 54-78 - [c70]Andrei C. Rusu, Katayoun Farrahi, Mahesan Niranjan:
Flattening the Curve Through Reinforcement Learning Driven Test and Trace Policies. PervasiveHealth 2022: 174-206 - 2021
- [j59]Xin Du, Katayoun Farrahi, Mahesan Niranjan:
Information Bottleneck Theory Based Exploration of Cascade Learning. Entropy 23(10): 1360 (2021) - [j58]Samantha Kanza, Colin Leonard Bird, Mahesan Niranjan, William McNeill, Jeremy Graham Frey:
The AI for Scientific Discovery Network+. Patterns 2(1): 100162 (2021) - [c69]Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim:
Depth Estimation from a Single Omnidirectional Image using Domain Adaptation. CVMP 2021: 3:1-3:9 - [c68]Premananth Gowtham, Mahesan Niranjan, Kaneswaran Anantharajah:
Automated gastrointestinal abnormalities detection from endoscopic images. ICIIS 2021: 191-196 - 2020
- [j57]Tristan Millington, Mahesan Niranjan:
Partial correlation financial networks. Appl. Netw. Sci. 5(1): 11 (2020) - [j56]Francisco Belchí Guillamón, Jacek Brodzki, Matthew Burfitt, Mahesan Niranjan:
A Numerical Measure of the Instability of Mapper-Type Algorithms. J. Mach. Learn. Res. 21: 202:1-202:45 (2020) - [j55]Donya Rahmani, Mahesan Niranjan, Damien Fay, Akiko Takeda, Jacek Brodzki:
Estimation of Gaussian mixture models via tensor moments with application to online learning. Pattern Recognit. Lett. 131: 285-292 (2020) - [i7]Ethan Harris, Antonia Marcu, Matthew Painter, Mahesan Niranjan, Adam Prügel-Bennett, Jonathon S. Hare:
Understanding and Enhancing Mixed Sample Data Augmentation. CoRR abs/2002.12047 (2020) - [i6]Manuel Nunes, Enrico H. Gerding, Frank McGroarty, Mahesan Niranjan:
Long short-term memory networks and laglasso for bond yield forecasting: Peeping inside the black box. CoRR abs/2005.02217 (2020) - [i5]Tristan Millington, Mahesan Niranjan:
Construction of Minimum Spanning Trees from Financial Returns using Rank Correlation. CoRR abs/2005.03963 (2020)
2010 – 2019
- 2019
- [j54]Gregory M. Parkes, Mahesan Niranjan:
Uncovering extensive post-translation regulation during human cell cycle progression by integrative multi-'omics analysis. BMC Bioinform. 20(1): 536:1-536:13 (2019) - [j53]Manuel Nunes, Enrico H. Gerding, Frank McGroarty, Mahesan Niranjan:
A comparison of multitask and single task learning with artificial neural networks for yield curve forecasting. Expert Syst. Appl. 119: 362-375 (2019) - [c67]Xin Du, Katayoun Farrahi, Mahesan Niranjan:
Transfer learning across human activities using a cascade neural network architecture. UbiComp 2019: 35-44 - [c66]Guillermo Romero Moreno, Mahesan Niranjan, Adam Prügel-Bennett:
Saliency Map on Cnns for Protein Secondary Structure Prediction. ICASSP 2019: 1249-1253 - [c65]Bahman Asadi, Mahesan Niranjan:
Representation-dimensionality Trade-off in Biological Sequence-based Inference. IJCNN 2019: 1-7 - [c64]Pratheeba Jeyananthan, Mahesan Niranjan:
Classification and Regression Analysis of Lung Tumors from Multi-level Gene Expression Data. IJCNN 2019: 1-8 - [c63]Tristan Millington, Mahesan Niranjan:
Quantifying Influence in Financial Markets via Partial Correlation Network Inference. ISPA 2019: 306-311 - [c62]Luis Montesdeoca, Steven Squires, Mahesan Niranjan:
Variational Autoencoder for Non-Negative Matrix Factorization with Exogenous Inputs Applied to Financial Data Modelling. ISPA 2019: 312-317 - [c61]Luis Montesdeoca, Mahesan Niranjan:
On Comparing the Influences of Exogenous Information on Bitcoin Prices and Stock Index Values. MARBLE 2019: 93-100 - [i4]Ethan Harris, Mahesan Niranjan, Jonathon S. Hare:
A Biologically Inspired Visual Working Memory for Deep Networks. CoRR abs/1901.03665 (2019) - [i3]Steven Squires, Adam Prügel-Bennett, Mahesan Niranjan:
Minimum description length as an objective function for non-negative matrix factorization. CoRR abs/1902.01632 (2019) - [i2]Francisco Belchí Guillamón, Jacek Brodzki, Matthew Burfitt, Mahesan Niranjan:
A numerical measure of the instability of Mapper-type algorithms. CoRR abs/1906.01507 (2019) - [i1]Steven Squires, Adam Prügel-Bennett, Mahesan Niranjan:
A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation. CoRR abs/1906.05912 (2019) - 2018
- [j52]Mariam Pirashvili, Lee Steinberg, Francisco Belchí Guillamón, Mahesan Niranjan, Jeremy G. Frey, Jacek Brodzki:
Improved understanding of aqueous solubility modeling through topological data analysis. J. Cheminformatics 10(1): 54:1-54:14 (2018) - [j51]Enrique S. Marquez, Jonathon S. Hare, Mahesan Niranjan:
Deep Cascade Learning. IEEE Trans. Neural Networks Learn. Syst. 29(11): 5475-5485 (2018) - 2017
- [j50]Steven Squires, Adam Prügel-Bennett, Mahesan Niranjan:
Rank Selection in Nonnegative Matrix Factorization using Minimum Description Length. Neural Comput. 29(8): 2164-2176 (2017) - [c60]Steven Squires, Rob M. Ewing, Adam Prügel-Bennett, Mahesan Niranjan:
A Method of Integrating Spatial Proteomics and Protein-Protein Interaction Network Data. ICONIP (5) 2017: 782-790 - [c59]Tristan Millington, Mahesan Niranjan:
Robust Portfolio Risk Minimization Using the Graphical Lasso. ICONIP (2) 2017: 863-872 - [c58]Steven Squires, Luis Montesdeoca, Adam Prügel-Bennett, Mahesan Niranjan:
Non-Negative Matrix Factorization with Exogenous Inputs for Modeling Financial Data. ICONIP (2) 2017: 873-881 - 2016
- [j49]Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan:
Rotation invariant texture descriptors based on Gaussian Markov random fields for classification. Pattern Recognit. Lett. 69: 15-21 (2016) - [c57]Luis Montesdeoca, Mahesan Niranjan:
Extending the feature set of a data-driven artificial neural network model of pricing financial options. SSCI 2016: 1-6 - 2015
- [j48]Haifen Chen, Jing Guo, Shital K. Mishra, Paul Robson, Mahesan Niranjan, Jie Zheng:
Single-cell transcriptional analysis to uncover regulatory circuits driving cell fate decisions in early mouse development. Bioinform. 31(7): 1060-1066 (2015) - [j47]Yawwani Gunawardana, Shuhei Fujiwara, Akiko Takeda, Jeongmin Woo, Christopher H. Woelk, Mahesan Niranjan:
Outlier detection at the transcriptome-proteome interface. Bioinform. 31(15): 2530-2536 (2015) - [j46]Thilini Nadungodage, Ruvan Weerasinghe, Mahesan Niranjan:
Speaker Adaptation Applied to Sinhala Speech Recognition. Int. J. Comput. Linguistics Appl. 6(1): 117-129 (2015) - [j45]Jonathon S. Hare, Sina Samangooei, Mahesan Niranjan, Nicholas Gibbins:
Detection of social events in streams of social multimedia. Int. J. Multim. Inf. Retr. 4(4): 289-302 (2015) - [j44]Abdullah Alrajeh, Mahesan Niranjan:
Scalable Reordering Models for SMT based on Multiclass SVM. Prague Bull. Math. Linguistics 103: 65-84 (2015) - [j43]Viraj Welgama, Ruvan Weerasinghe, Mahesan Niranjan:
Defining the Gold Standard Definitions for the Morphology of Sinhala Words. Res. Comput. Sci. 90: 163-171 (2015) - [c56]Randil Pushpananda, Ruvan Weerasinghe, Mahesan Niranjan:
Statistical Machine Translation from and into Morphologically Rich and Low Resourced Languages. CICLing (1) 2015: 545-556 - [c55]Avi Rosenfeld, David G. Graham, Rifat A. Hamoudi, Rommel Butawan, Victor Eneh, Saif Khan, Haroon Miah, Mahesan Niranjan, Laurence B. Lovat:
MIAT: A novel attribute selection approach to better predict upper gastrointestinal cancer. DSAA 2015: 1-7 - 2014
- [j42]Kaya Kuru, Mahesan Niranjan, Yusuf Tunca, Erhan Osvank, Tayyaba Azim:
Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics. Artif. Intell. Medicine 62(2): 105-118 (2014) - [j41]Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan:
Gaussian Markov random field based improved texture descriptor for image segmentation. Image Vis. Comput. 32(11): 884-895 (2014) - [c54]Randil Pushpananda, Ruvan Weerasinghe, Mahesan Niranjan:
Sinhala-Tamil Machine Translation: Towards better Translation Quality. ALTA 2014: 129-133 - [c53]Abdullah Alrajeh, Mahesan Niranjan:
Large-scale Reordering Model for Statistical Machine Translation using Dual Multinomial Logistic Regression. EMNLP 2014: 1758-1763 - [c52]Abdullah Alrajeh, Akiko Takeda, Mahesan Niranjan:
Memory-efficient large-scale linear support vector machine. ICMV 2014: 944527 - [c51]Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan:
An Inhomogeneous Bayesian Texture Model for Spatially Varying Parameter Estimation. ICPRAM 2014: 139-146 - [c50]Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan:
Quantitative Analysis of Pulmonary Emphysema using Isotropic Gaussian Markov Random Fields. VISAPP (3) 2014: 44-53 - [c49]Tayyaba Azim, Mahesan Niranjan:
Computational Models of Object Recognition - Goal, Role and Success. VISAPP (1) 2014: 179-186 - [c48]Tayyaba Azim, Mahesan Niranjan:
Texture Classification with Fisher Kernel Extracted from the Continuous Models of RBM. VISAPP (2) 2014: 684-690 - [c47]Abdullah Alrajeh, Mahesan Niranjan:
Bayesian Reordering Model with Feature Selection. WMT@ACL 2014: 477-485 - 2013
- [j40]Yawwani Gunawardana, Mahesan Niranjan:
Bridging the gap between transcriptome and proteome measurements identifies post-translationally regulated genes. Bioinform. 29(23): 3060-3066 (2013) - [j39]Akiko Takeda, Mahesan Niranjan, Jun-ya Gotoh, Yoshinobu Kawahara:
Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios. Comput. Manag. Sci. 10(1): 21-49 (2013) - [j38]Taihai Chen, Evangelos B. Mazomenos, Koushik Maharatna, Srinandan Dasmahapatra, Mahesan Niranjan:
Design of a Low-Power On-Body ECG Classifier for Remote Cardiovascular Monitoring Systems. IEEE J. Emerg. Sel. Topics Circuits Syst. 3(1): 75-85 (2013) - [j37]Ali Hassan, Robert I. Damper, Mahesan Niranjan:
On Acoustic Emotion Recognition: Compensating for Covariate Shift. IEEE Trans. Speech Audio Process. 21(7): 1458-1468 (2013) - [c46]Tim Matthews, Mark S. Nixon, Mahesan Niranjan:
Enriching Texture Analysis with Semantic Data. CVPR 2013: 1248-1255 - [c45]Piyushkumar A. Mundra, Jie Zheng, Mahesan Niranjan, Roy E. Welsch, Jagath C. Rajapakse:
Inferring Time-Delayed Gene Regulatory Networks Using Cross-Correlation and Sparse Regression. ISBRA 2013: 64-75 - [c44]Sina Samangooei, Jonathon S. Hare, David Dupplaw, Mahesan Niranjan, Nicholas Gibbins, Paul H. Lewis, Jamie Davies, Neha Jain, John Preston:
Social Event Detection Via Sparse Multi-modal Feature Selection and Incremental Density Based Clustering. MediaEval 2013 - [c43]Tayyaba Azim, Mahesan Niranjan:
Inducing discrimination in biologically inspired models of visual scene recognition. MLSP 2013: 1-6 - [c42]B. Mayurathan, U. A. J. Pinidiyaarachchi, Mahesan Niranjan:
Compact codebook design for visual scene recognition by Sequential Input Space Carving. MLSP 2013: 1-6 - 2012
- [j36]Wei Liu, Mahesan Niranjan:
Gaussian process modelling for bicoid mRNA regulation in spatio-temporal Bicoid profile. Bioinform. 28(3): 366-372 (2012) - [j35]Xin Liu, Mahesan Niranjan:
State and parameter estimation of the heat shock response system using Kalman and particle filters. Bioinform. 28(11): 1501-1507 (2012) - [j34]Ke Yuan, Mark A. Girolami, Mahesan Niranjan:
Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations. Neural Comput. 24(6): 1462-1486 (2012) - [j33]Amirthalingam Ramanan, Mahesan Niranjan:
A Review of Codebook Models in Patch-Based Visual Object Recognition. J. Signal Process. Syst. 68(3): 333-352 (2012) - [c41]Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan:
Unsupervised Texture Segmentation using Active Contours and Local Distributions of Gaussian Markov Random Field Parameters. BMVC 2012: 1-11 - [c40]Kaya Kuru, Mahesan Niranjan, Yusuf Tunca:
Establishment of a Diagnostic Decision Support System in Genetic Dysmorphology. ICMLA (2) 2012: 164-169 - [c39]Taihai Chen, Evangelos B. Mazomenos, Koushik Maharatna, Srinandan Dasmahapatra, Mahesan Niranjan:
On the Trade-Off of Accuracy and Computational Complexity for Classifying Normal and Abnormal ECG in Remote CVD Monitoring Systems. SiPS 2012: 37-42 - 2011
- [j32]Yizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan:
Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation. J. Mach. Learn. Res. 12: 1-30 (2011) - [j31]Andrew Zammit-Mangion, Ke Yuan, Visakan Kadirkamanathan, Mahesan Niranjan, Guido Sanguinetti:
Online Variational Inference for State-Space Models with Point-Process Observations. Neural Comput. 23(8): 1967-1999 (2011) - 2010
- [j30]Salih Tuna, Mahesan Niranjan:
Reducing the algorithmic variability in transcriptome-based inference. Bioinform. 26(9): 1185-1191 (2010) - [j29]Ivan Markovsky, Mahesan Niranjan:
Approximate low-rank factorization with structured factors. Comput. Stat. Data Anal. 54(12): 3411-3420 (2010) - [j28]Yizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan:
The application of structured learning in natural language processing. Mach. Transl. 24(2): 71-85 (2010) - [j27]Ke Yuan, Mahesan Niranjan:
Estimating a State-Space Model from Point Process Observations: A Note on Convergence. Neural Comput. 22(8): 1993-2001 (2010) - [j26]Weichao Xu, Y. S. Hung, Mahesan Niranjan, Minfen Shen:
Asymptotic mean and variance of Gini correlation for bivariate normal samples. IEEE Trans. Signal Process. 58(2): 522-534 (2010) - [j25]Salih Tuna, Mahesan Niranjan:
Inference from Low Precision Transcriptome Data Representation. J. Signal Process. Syst. 58(3): 267-279 (2010) - [c38]Yizhao Ni, Mahesan Niranjan:
Exploiting Long-Range Dependencies in Protein beta-Sheet Secondary Structure Prediction. PRIB 2010: 349-357
2000 – 2009
- 2009
- [j24]Daniela Wieser, Mahesan Niranjan:
Remote Homology Detection Using a Kernel Method that Combines Sequence and Secondary-Structure Similarity Scores. Silico Biol. 9(3): 89-103 (2009) - [c37]Yizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan:
Handling phrase reorderings for machine translation. ACL/IJCNLP (2) 2009: 241-244 - [c36]C. Q. Chang, Y. S. Hung, Mahesan Niranjan:
Modelling uncertainty in transcriptome measurements enhances network component analysis of yeast metabolic cycle. ICASSP 2009: 1769-1772 - [c35]Bassam Farran, Amirthalingam Ramanan, Mahesan Niranjan:
Sequential Hierarchical Pattern Clustering. PRIB 2009: 79-88 - [c34]Salih Tuna, Mahesan Niranjan:
Cross-Platform Analysis with Binarized Gene Expression Data. PRIB 2009: 439-449 - [e2]Visakan Kadirkamanathan, Guido Sanguinetti, Mark A. Girolami, Mahesan Niranjan, Josselin Noirel:
Pattern Recognition in Bioinformatics, 4th IAPR International Conference, PRIB 2009, Sheffield, UK, September 7-9, 2009. Proceedings. Lecture Notes in Computer Science 5780, Springer 2009, ISBN 978-3-642-04030-6 [contents] - 2008
- [j23]Renata da Silva Camargo, Mahesan Niranjan:
Mining Protein Database using Machine Learning Techniques. J. Integr. Bioinform. 5(2) (2008) - [j22]Sujimarn Suwannaroj, Mahesan Niranjan:
Enhancing Automatic Construction of Gene Subnetworks by Integrating Multiple Sources of Information. J. Signal Process. Syst. 50(3): 331-340 (2008) - [c33]Yang Zhang, Hongyu Li, Mahesan Niranjan, Peter I. Rockett:
Applying Cost-Sensitive Multiobjective Genetic Programming to Feature Extraction for Spam E-mail Filtering. EuroGP 2008: 325-336 - 2007
- [j21]Anastasia Samsonova, Mahesan Niranjan, Steven Russell, Alvis Brazma:
Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster. PLoS Comput. Biol. 3(7) (2007) - 2006
- [c32]Hongyu Li, Mahesan Niranjan:
Outlier Detection in Benchmark Classification Tasks. ICASSP (5) 2006: 557-560 - [c31]Anjali Bharatkumar Samani, Joab R. Winkler, Mahesan Niranjan:
Automatic Face Recognition Using Stereo Images. ICASSP (5) 2006: 913-916 - 2005
- [e1]