default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDDavid S. Doermann
Person information
- affiliation: University at Buffalo, USA
- affiliation (former): University of Maryland, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[b1]Baochang Zhang, Tiancheng Wang, Sheng Xu, David S. Doermann:
Neural Networks with Model Compression. Springer 2024, ISBN 978-981-99-5067-6, pp. 1-260- [j64]Jaakko J. Sauvola, Sasu Tarkoma, Mika Klemettinen, Jukka Riekki, David S. Doermann:
Future of software development with generative AI. Autom. Softw. Eng. 31(1): 26 (2024) - [j63]Alireza Alaei
, Vinh Bui, David S. Doermann, Umapada Pal:
Document Image Quality Assessment: A Survey. ACM Comput. Surv. 56(2): 29:1-29:36 (2024) - [j62]Anurag Dhote, Mohammed Javed, David S. Doermann:
Swin-chart: An efficient approach for chart classification. Pattern Recognit. Lett. 185: 203-209 (2024) - [c229]Xuan Gong, Shanglin Li, Yuxiang Bao, Barry Yao, Yawen Huang, Ziyan Wu, Baochang Zhang, Yefeng Zheng, David S. Doermann:
Federated Learning via Input-Output Collaborative Distillation. AAAI 2024: 22058-22066 - [c228]Pengyu Yan, Mahesh Bhosale, Jay Lal, Bikhyat Adhikari, David S. Doermann:
ChartReformer: Natural Language-Driven Chart Image Editing. ICDAR (1) 2024: 453-469 - [c227]Sheng Xu, Mingze Wang, Yanjing Li, Mingbao Lin, Baochang Zhang, David S. Doermann, Xiao Sun:
Learning 1-Bit Tiny Object Detector with Discriminative Feature Refinement. ICML 2024 - [i55]Pengyu Yan, Mahesh Bhosale, Jay Lal, Bikhyat Adhikari, David S. Doermann:
ChartReformer: Natural Language-Driven Chart Image Editing. CoRR abs/2403.00209 (2024) - [i54]Yangcen Liu, Ziyi Liu, Yuanhao Zhai, Wen Li, David S. Doermann, Junsong Yuan:
STAT: Towards Generalizable Temporal Action Localization. CoRR abs/2404.13311 (2024) - [i53]Saurav Sagar, Mohammed Javed, David S. Doermann:
Leaf-Based Plant Disease Detection and Explainable AI. CoRR abs/2404.16833 (2024) - [i52]Jihao Qiu, Yuan Zhang, Xi Tang, Lingxi Xie, Tianren Ma, Pengyu Yan, David S. Doermann, Qixiang Ye, Yunjie Tian:
Artemis: Towards Referential Understanding in Complex Videos. CoRR abs/2406.00258 (2024) - [i51]Yuanhao Zhai, Kevin Lin, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Chung-Ching Lin, David S. Doermann, Junsong Yuan, Lijuan Wang:
Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation. CoRR abs/2406.06890 (2024) - [i50]Tianren Ma, Lingxi Xie, Yunjie Tian, Boyu Yang, Yuan Zhang, David S. Doermann, Qixiang Ye:
ClawMachine: Fetching Visual Tokens as An Entity for Referring and Grounding. CoRR abs/2406.11327 (2024) - [i49]Yuanhao Zhai, Kevin Lin, Linjie Li, Chung-Ching Lin, Jianfeng Wang, Zhengyuan Yang, David S. Doermann, Junsong Yuan, Zicheng Liu, Lijuan Wang:
IDOL: Unified Dual-Modal Latent Diffusion for Human-Centric Joint Video-Depth Generation. CoRR abs/2407.10937 (2024) - 2023
- [j61]Runqi Wang, Zhen Liu, Baochang Zhang, Guodong Guo, David S. Doermann:
Few-Shot Learning with Complex-Valued Neural Networks and Dependable Learning. Int. J. Comput. Vis. 131(1): 385-404 (2023) - [j60]Runqi Wang, Linlin Yang, Hanlin Chen, Wei Wang, David S. Doermann, Baochang Zhang:
Anti-Bandit for Neural Architecture Search. Int. J. Comput. Vis. 131(10): 2682-2698 (2023) - [j59]Yuanhao Zhai, Le Wang, Wei Tang, Qilin Zhang, Nanning Zheng, David S. Doermann, Junsong Yuan, Gang Hua:
Adaptive Two-Stream Consensus Network for Weakly-Supervised Temporal Action Localization. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4136-4151 (2023) - [j58]Xuan Gong, Liangchen Song, Rishi Vedula, Abhishek Sharma, Meng Zheng, Benjamin Planche, Arun Innanje, Terrence Chen, Junsong Yuan, David S. Doermann, Ziyan Wu:
Federated Learning With Privacy-Preserving Ensemble Attention Distillation. IEEE Trans. Medical Imaging 42(7): 2057-2067 (2023) - [c226]Xuan Gong, Liangchen Song, Meng Zheng, Benjamin Planche, Terrence Chen, Junsong Yuan, David S. Doermann, Ziyan Wu:
Progressive Multi-View Human Mesh Recovery with Self-Supervision. AAAI 2023: 676-684 - [c225]Yuanhao Zhai, Ziyi Liu, Zhenyu Wu, Yi Wu, Chunluan Zhou, David S. Doermann, Junsong Yuan, Gang Hua:
SOAR: Scene-debiasing Open-set Action Recognition. ICCV 2023: 10210-10220 - [c224]Yuanhao Zhai, Tianyu Luan, David S. Doermann, Junsong Yuan:
Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning. ICCV 2023: 22333-22343 - [c223]Anurag Dhote, Mohammed Javed, David S. Doermann:
A Survey and Approach to Chart Classification. ICDAR Workshops (1) 2023: 67-82 - [c222]Saleem Ahmed, Pengyu Yan, David S. Doermann, Srirangaraj Setlur, Venu Govindaraju:
SpaDen: Sparse and Dense Keypoint Estimation for Real-World Chart Understanding. ICDAR (2) 2023: 77-93 - [c221]Pengyu Yan, Saleem Ahmed, David S. Doermann:
Context-Aware Chart Element Detection. ICDAR (1) 2023: 218-233 - [c220]Jay Lal, Aditya Mitkari, Mahesh Bhosale, David S. Doermann:
LineFormer: Line Chart Data Extraction Using Instance Segmentation. ICDAR (5) 2023: 387-400 - [c219]Liangchen Song, Xuan Gong, Helong Zhou, Jiajie Chen, Qian Zhang, David S. Doermann, Junsong Yuan:
Exploring the Knowledge Transferred by Response-Based Teacher-Student Distillation. ACM Multimedia 2023: 2704-2713 - [c218]Yuanhao Zhai, Mingzhen Huang, Tianyu Luan, Lu Dong, Ifeoma Nwogu, Siwei Lyu, David S. Doermann, Junsong Yuan:
Language-guided Human Motion Synthesis with Atomic Actions. ACM Multimedia 2023: 5262-5271 - [c217]Zhenyi Wang, Li Shen, Tongliang Liu, Tiehang Duan, Yanjun Zhu, Donglin Zhan, David S. Doermann, Mingchen Gao:
Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training. NeurIPS 2023 - [i48]Jay Lal, Aditya Mitkari, Mahesh Bhosale, David S. Doermann:
LineFormer: Rethinking Line Chart Data Extraction as Instance Segmentation. CoRR abs/2305.01837 (2023) - [i47]Pengyu Yan, Saleem Ahmed, David S. Doermann:
Context-Aware Chart Element Detection. CoRR abs/2305.04151 (2023) - [i46]Shaohui Lin, Wenxuan Huang, Jiao Xie, Baochang Zhang, Yunhang Shen, Zhou Yu, Jungong Han, David S. Doermann:
Filter Pruning for Efficient CNNs via Knowledge-driven Differential Filter Sampler. CoRR abs/2307.00198 (2023) - [i45]Anurag Dhote, Mohammed Javed, David S. Doermann:
A Survey and Approach to Chart Classification. CoRR abs/2307.04147 (2023) - [i44]Anurag Dhote, Mohammed Javed, David S. Doermann:
A Survey on Figure Classification Techniques in Scientific Documents. CoRR abs/2307.05694 (2023) - [i43]Abhinandan Kumar Pun, Mohammed Javed, David S. Doermann:
A Survey on Change Detection Techniques in Document Images. CoRR abs/2307.07691 (2023) - [i42]Saleem Ahmed, Pengyu Yan, David S. Doermann, Srirangaraj Setlur, Venu Govindaraju:
SpaDen : Sparse and Dense Keypoint Estimation for Real-World Chart Understanding. CoRR abs/2308.01971 (2023) - [i41]Yuanhao Zhai, Mingzhen Huang, Tianyu Luan, Lu Dong, Ifeoma Nwogu, Siwei Lyu, David S. Doermann, Junsong Yuan:
Language-guided Human Motion Synthesis with Atomic Actions. CoRR abs/2308.09611 (2023) - [i40]Yuanhao Zhai, Tianyu Luan, David S. Doermann, Junsong Yuan:
Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning. CoRR abs/2309.01246 (2023) - [i39]Yuanhao Zhai, Ziyi Liu, Zhenyu Wu, Yi Wu, Chunluan Zhou, David S. Doermann, Junsong Yuan, Gang Hua:
SOAR: Scene-debiasing Open-set Action Recognition. CoRR abs/2309.01265 (2023) - [i38]Mahesh Bhosale, Abhishek Kumar, David S. Doermann:
Player Re-Identification Using Body Part Appearences. CoRR abs/2310.14469 (2023) - [i37]Nikhil Manali, David S. Doermann, Mahesh Desai:
The Analysis and Extraction of Structure from Organizational Charts. CoRR abs/2311.10234 (2023) - [i36]Xuan Gong, Shanglin Li, Yuxiang Bao, Barry Yao, Yawen Huang, Ziyan Wu, Baochang Zhang, Yefeng Zheng, David S. Doermann:
Federated Learning via Input-Output Collaborative Distillation. CoRR abs/2312.14478 (2023) - 2022
- [j57]Junhe Zhao, Sheng Xu, Baochang Zhang, Jiaxin Gu, David S. Doermann, Guodong Guo:
Towards Compact 1-bit CNNs via Bayesian Learning. Int. J. Comput. Vis. 130(2): 201-225 (2022) - [j56]Palaiahnakote Shivakumara, Pinaki Nath Chowdhury, Umapada Pal, David S. Doermann, Raghavendra Ramachandra, Tong Lu, Michael Blumenstein:
A Knowledge Enforcement Network-Based Approach for Classifying a Photographer's Images. Int. J. Pattern Recognit. Artif. Intell. 36(15): 2250046:1-2250046:29 (2022) - [j55]Jarkko Hyysalo, Sandun Dasanayake, Jari Hannu, Christian Schuss, Mikko Rajanen, Teemu Leppänen, David S. Doermann, Jaakko J. Sauvola:
Smart mask - Wearable IoT solution for improved protection and personal health. Internet Things 18: 100511 (2022) - [j54]Junhe Zhao, Sheng Xu, Runqi Wang, Baochang Zhang, Guodong Guo, David S. Doermann, Dianmin Sun:
Data-adaptive binary neural networks for efficient object detection and recognition. Pattern Recognit. Lett. 153: 239-245 (2022) - [j53]Zhibo Zhang, Yanjun Zhu, Rahul Rai, David S. Doermann:
PIMNet: Physics-Infused Neural Network for Human Motion Prediction. IEEE Robotics Autom. Lett. 7(4): 8949-8955 (2022) - [j52]Huan Chang, Yicheng Chen, Baochang Zhang, David S. Doermann:
Multi-UAV Mobile Edge Computing and Path Planning Platform Based on Reinforcement Learning. IEEE Trans. Emerg. Top. Comput. Intell. 6(3): 489-498 (2022) - [j51]Mingyuan Mao, Yuxin Tian, Baochang Zhang, Qixiang Ye, Wanquan Liu, David S. Doermann:
iffDetector: Inference-Aware Feature Filtering for Object Detection. IEEE Trans. Neural Networks Learn. Syst. 33(11): 6494-6503 (2022) - [j50]Sheng Xu, Chang Liu, Baochang Zhang, Jinhu Lü, Guodong Guo, David S. Doermann:
BiRe-ID: Binary Neural Network for Efficient Person Re-ID. ACM Trans. Multim. Comput. Commun. Appl. 18(1s): 26:1-26:22 (2022) - [c216]Xuan Gong, Abhishek Sharma, Srikrishna Karanam, Ziyan Wu, Terrence Chen, David S. Doermann, Arun Innanje:
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation. AAAI 2022: 11891-11899 - [c215]Sicheng Gao, Yutang Feng, Linlin Yang, Xuhui Liu, Zichen Zhu, David S. Doermann, Baochang Zhang:
MagFormer: Hybrid Video Motion Magnification Transformer from Eulerian and Lagrangian Perspectives. BMVC 2022: 444 - [c214]Xuan Gong, Meng Zheng, Benjamin Planche, Srikrishna Karanam, Terrence Chen, David S. Doermann, Ziyan Wu:
Self-supervised Human Mesh Recovery with Cross-Representation Alignment. ECCV (1) 2022: 212-230 - [c213]Liangchen Song, Xuan Gong, Benjamin Planche, Meng Zheng, David S. Doermann, Junsong Yuan, Terrence Chen, Ziyan Wu:
PREF: Predictability Regularized Neural Motion Fields. ECCV (22) 2022: 664-681 - [c212]Xuan Gong, Luckyson Khaidem, Wentao Zhu, Baochang Zhang, David S. Doermann:
Uncertainty Learning towards Unsupervised Deformable Medical Image Registration. WACV 2022: 1555-1564 - [i35]Runqi Wang, Linlin Yang, Baochang Zhang, Wentao Zhu, David S. Doermann, Guodong Guo:
Confidence Dimension for Deep Learning based on Hoeffding Inequality and Relative Evaluation. CoRR abs/2203.09082 (2022) - [i34]Xuan Gong, Meng Zheng, Benjamin Planche, Srikrishna Karanam, Terrence Chen, David S. Doermann, Ziyan Wu:
Self-supervised Human Mesh Recovery with Cross-Representation Alignment. CoRR abs/2209.04596 (2022) - [i33]Xuan Gong, Abhishek Sharma, Srikrishna Karanam, Ziyan Wu, Terrence Chen, David S. Doermann, Arun Innanje:
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation. CoRR abs/2209.04599 (2022) - [i32]Liangchen Song, Xuan Gong, Benjamin Planche, Meng Zheng, David S. Doermann, Junsong Yuan, Terrence Chen, Ziyan Wu:
PREF: Predictability Regularized Neural Motion Fields. CoRR abs/2209.10691 (2022) - [i31]Xuan Gong, Liangchen Song, Rishi Vedula, Abhishek Sharma, Meng Zheng, Benjamin Planche, Arun Innanje, Terrence Chen, Junsong Yuan, David S. Doermann, Ziyan Wu:
Federated Learning with Privacy-Preserving Ensemble Attention Distillation. CoRR abs/2210.08464 (2022) - [i30]Xuan Gong, Liangchen Song, Meng Zheng, Benjamin Planche, Terrence Chen, Junsong Yuan, David S. Doermann, Ziyan Wu:
Progressive Multi-view Human Mesh Recovery with Self-Supervision. CoRR abs/2212.05223 (2022) - 2021
- [j49]Song Xue, Hanlin Chen, Chunyu Xie, Baochang Zhang, Xuan Gong, David S. Doermann:
Fast and Unsupervised Neural Architecture Evolution for Visual Representation Learning. IEEE Comput. Intell. Mag. 16(3): 22-32 (2021) - [j48]Hanlin Chen, Li'an Zhuo, Baochang Zhang, Xiawu Zheng, Jianzhuang Liu, Rongrong Ji, David S. Doermann, Guodong Guo:
Binarized Neural Architecture Search for Efficient Object Recognition. Int. J. Comput. Vis. 129(2): 501-516 (2021) - [j47]Chunlei Liu, Wenrui Ding, Yuan Hu, Baochang Zhang, Jianzhuang Liu, Guodong Guo, David S. Doermann:
Rectified Binary Convolutional Networks with Generative Adversarial Learning. Int. J. Comput. Vis. 129(4): 998-1012 (2021) - [j46]Zhibo Zhang, Rahul Rai, Souma Chowdhury, David S. Doermann:
MIDPhyNet: Memorized infusion of decomposed physics in neural networks to model dynamic systems. Neurocomputing 428: 116-129 (2021) - [j45]Kenny Davila, Srirangaraj Setlur, David S. Doermann, Bhargava Urala Kota, Venu Govindaraju:
Chart Mining: A Survey of Methods for Automated Chart Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 43(11): 3799-3819 (2021) - [j44]Duona Zhang, Wenrui Ding, Baochang Zhang, Chunhui Liu, Jungong Han, David S. Doermann:
Learning modulation filter networks for weak signal detection in noise. Pattern Recognit. 109: 107590 (2021) - [c211]Sheng Xu, Junhe Zhao, Jinhu Lu, Baochang Zhang, Shumin Han, David S. Doermann:
Layer-Wise Searching for 1-Bit Detectors. CVPR 2021: 5682-5691 - [c210]Bulla Rajesh, Priyanshu Jain, Mohammed Javed, David S. Doermann:
HH-CompWordNet: Holistic Handwritten Word Recognition in the Compressed Domain. DCC 2021: 362 - [c209]Song Xue, Runqi Wang, Baochang Zhang, Tian Wang, Guodong Guo, David S. Doermann:
IDARTS: Interactive Differentiable Architecture Search. ICCV 2021: 1143-1152 - [c208]Xuan Gong, Abhishek Sharma, Srikrishna Karanam, Ziyan Wu, Terrence Chen, David S. Doermann, Arun Innanje:
Ensemble Attention Distillation for Privacy-Preserving Federated Learning. ICCV 2021: 15056-15066 - [c207]Shuwei Shao, Zhongcai Pei, Weihai Chen, Baochang Zhang, Xingming Wu, Dianmin Sun, David S. Doermann:
Self-Supervised Learning for Monocular Depth Estimation on Minimally Invasive Surgery Scenes. ICRA 2021: 7159-7165 - [c206]Leighton Collins, Payam Ghassemi, Ehsan Tarkesh Esfahani, David S. Doermann, Karthik Dantu, Souma Chowdhury:
Scalable Coverage Path Planning of Multi-Robot Teams for Monitoring Non-Convex Areas. ICRA 2021: 7393-7399 - [c205]Junhe Zhao, Linlin Yang, Baochang Zhang, Guodong Guo, David S. Doermann:
Uncertainty-aware Binary Neural Networks. IJCAI 2021: 3441-3447 - [c204]Amir Behjat, Hemanth Manjunatha, Prajit KrisshnaKumar, Apurv Jani, Leighton Collins, Payam Ghassemi, Joseph P. Distefano, David S. Doermann, Karthik Dantu, Ehsan Tarkesh Esfahani, Souma Chowdhury:
Learning Robot Swarm Tactics over Complex Adversarial Environments. MRS 2021: 83-91 - [c203]Joseph P. Distefano, Hemanth Manjunatha, Souma Chowdhury, Karthik Dantu, David S. Doermann, Ehsan Tarkesh Esfahani:
Using Physiological Information to Classify Task Difficulty in Human-Swarm Interaction. SMC 2021: 1198-1203 - [c202]Xuan Gong, Shuyan Chen, Baochang Zhang, David S. Doermann:
Style Consistent Image Generation for Nuclei Instance Segmentation. WACV 2021: 3993-4002 - [c201]Xuan Gong, Xin Xia, Wentao Zhu, Baochang Zhang, David S. Doermann, Li'an Zhuo:
Deformable Gabor Feature Networks for Biomedical Image Classification. WACV 2021: 4003-4011 - [i29]Huan Chang, Yicheng Chen, Baochang Zhang, David S. Doermann:
Multi-UAV Mobile Edge Computing and Path Planning Platform based on Reinforcement Learning. CoRR abs/2102.02078 (2021) - [i28]Leighton Collins, Payam Ghassemi, Ehsan Tarkesh Esfahani, David S. Doermann, Karthik Dantu, Souma Chowdhury:
Scalable Coverage Path Planning of Multi-Robot Teams for Monitoring Non-Convex Areas. CoRR abs/2103.14709 (2021) - [i27]Mingyuan Mao, Baochang Zhang, David S. Doermann, Jie Guo, Shumin Han, Yuan Feng, Xiaodi Wang, Errui Ding:
Probabilistic Ranking-Aware Ensembles for Enhanced Object Detections. CoRR abs/2105.03139 (2021) - [i26]Teli Ma, Mingyuan Mao, Honghui Zheng, Peng Gao, Xiaodi Wang, Shumin Han, Errui Ding, Baochang Zhang, David S. Doermann:
Oriented Object Detection with Transformer. CoRR abs/2106.03146 (2021) - [i25]Runqi Wang, Baochang Zhang, Li'an Zhuo, Qixiang Ye, David S. Doermann:
Cogradient Descent for Dependable Learning. CoRR abs/2106.10617 (2021) - [i24]Yuanhao Zhai, Le Wang, David S. Doermann, Junsong Yuan:
Two-Stream Consensus Network: Submission to HACS Challenge 2021 Weakly-Supervised Learning Track. CoRR abs/2106.10829 (2021) - [i23]Amir Behjat, Hemanth Manjunatha, Prajit KrisshnaKumar, Apurv Jani, Leighton Collins, Payam Ghassemi, Joseph P. Distefano, David S. Doermann, Karthik Dantu, Ehsan Tarkesh Esfahani, Souma Chowdhury:
Learning Robot Swarm Tactics over Complex Adversarial Environments. CoRR abs/2109.05663 (2021) - [i22]Joseph P. Distefano, Hemanth Manjunatha, Souma Chowdhury, Karthik Dantu, David S. Doermann, Ehsan Tarkesh Esfahani:
Using Physiological Information to Classify Task Difficulty in Human-Swarm Interaction. CoRR abs/2109.12055 (2021) - [i21]Runqi Wang, Xiaoyue Duan, Baochang Zhang, Song Xue, Wentao Zhu, David S. Doermann, Guodong Guo:
Associative Adversarial Learning Based on Selective Attack. CoRR abs/2112.13989 (2021) - 2020
- [j43]Amir Behjat, Chen Zeng, Rahul Rai, Ion Matei, David S. Doermann, Souma Chowdhury:
A physics-aware learning architecture with input transfer networks for predictive modeling. Appl. Soft Comput. 96: 106665 (2020) - [j42]Chunlei Liu, Wenrui Ding, Yuan Hu, Xin Xia, Baochang Zhang, Jianzhuang Liu, David S. Doermann:
Circulant Binary Convolutional Networks for Object Recognition. IEEE J. Sel. Top. Signal Process. 14(4): 884-893 (2020) - [c200]Hanlin Chen, Li'an Zhuo, Baochang Zhang, Xiawu Zheng, Jianzhuang Liu, David S. Doermann, Rongrong Ji:
Binarized Neural Architecture Search. AAAI 2020: 10526-10533 - [c199]Li'an Zhuo, Baochang Zhang, Linlin Yang, Hanlin Chen, Qixiang Ye, David S. Doermann, Rongrong Ji, Guodong Guo:
Cogradient Descent for Bilinear Optimization. CVPR 2020: 7956-7964 - [c198]Hanlin Chen, Baochang Zhang, Song Xue, Xuan Gong, Hong Liu, Rongrong Ji, David S. Doermann:
Anti-bandit Neural Architecture Search for Model Defense. ECCV (13) 2020: 70-85 - [c197]Yutao Hu, Xiaolong Jiang, Xuhui Liu, Baochang Zhang, Jungong Han, Xianbin Cao, David S. Doermann:
NAS-Count: Counting-by-Density with Neural Architecture Search. ECCV (22) 2020: 747-766 - [c196]Chao Fang, Yutao Hu, Baochang Zhang, David S. Doermann:
The Fusion of Neural Architecture Search and Destruction and Construction Learning - First Classified. ICPR Workshops (8) 2020: 480-489 - [c195]Yanjun Zhu, David S. Doermann, Yanxia Zhang, Qiong Liu, Andreas Girgensohn:
What and How? Jointly Forecasting Human Action and Pose. ICPR 2020: 771-778 - [c194]Li'an Zhuo, Baochang Zhang, Hanlin Chen, Linlin Yang, Chen Chen, Yanjun Zhu, David S. Doermann:
CP-NAS: Child-Parent Neural Architecture Search for 1-bit CNNs. IJCAI 2020: 1033-1039 - [c193]Hemanth Manjunatha, Joseph P. Distefano, Apurv Jani, Payam Ghassemi, Souma Chowdhury, Karthik Dantu, David S. Doermann, Ehsan Tarkesh Esfahani:
Using Physiological Measurements to Analyze the Tactical Decisions in Human Swarm Teams. SMC 2020: 256-261 - [c192]Teli Ma, Yizhi Wang, Jinxin Shao, Baochang Zhang, David S. Doermann:
Orthogonal Features Fusion Network for Anomaly Detection. VCIP 2020: 33-37 - [i20]Yutao Hu, Xiaolong Jiang, Xuhui Liu, Baochang Zhang, Jungong Han, Xianbin Cao, David S. Doermann:
NAS-Count: Counting-by-Density with Neural Architecture Search. CoRR abs/2003.00217 (2020) - [i19]Li'an Zhuo, Baochang Zhang, Hanlin Chen, Linlin Yang, Chen Chen, Yanjun Zhu, David S. Doermann:
CP-NAS: Child-Parent Neural Architecture Search for Binary Neural Networks. CoRR abs/2005.00057 (2020) - [i18]Li'an Zhuo, Baochang Zhang, Linlin Yang, Hanlin Chen, Qixiang Ye, David S. Doermann, Guodong Guo, Rongrong Ji:
Cogradient Descent for Bilinear Optimization. CoRR abs/2006.09142 (2020) - [i17]Mingyuan Mao, Yuxin Tian, Baochang Zhang, Qixiang Ye, Wanquan Liu, Guodong Guo, David S. Doermann:
iffDetector: Inference-aware Feature Filtering for Object Detection. CoRR abs/2006.12708 (2020) - [i16]Hanlin Chen, Baochang Zhang, Song Xue, Xuan Gong, Hong Liu, Rongrong Ji, David S. Doermann:
Anti-Bandit Neural Architecture Search for Model Defense. CoRR abs/2008.00698 (2020) - [i15]Hanlin Chen, Li'an Zhuo, Baochang Zhang, Xiawu Zheng, Jianzhuang Liu, Rongrong Ji, David S. Doermann, Guodong Guo:
Binarized Neural Architecture Search for Efficient Object Recognition. CoRR abs/2009.04247 (2020) - [i14]Wenyu Zhao, Teli Ma, Xuan Gong, Baochang Zhang, David S. Doermann:
A Review of Recent Advances of Binary Neural Networks for Edge Computing. CoRR abs/2011.14824 (2020) - [i13]Xuan Gong, Xin Xia, Wentao Zhu, Baochang Zhang, David S. Doermann, Lian Zhuo:
Deformable Gabor Feature Networks for Biomedical Image Classification. CoRR abs/2012.04109 (2020)
2010 – 2019
- 2019
- [j41]Sungmin Eum, David S. Doermann:
Planar content selection in images and videos using frontalness. Pattern Recognit. Lett. 124: 55-62 (2019) - [j40]Showmik Bhowmik, Ram Sarkar, Bishwadeep Das, David S. Doermann:
GiB: A Game Theory Inspired Binarization Technique for Degraded Document Images. IEEE Trans. Image Process. 28(3): 1443-1455 (2019) - [c191]Jiaxin Gu, Ce Li, Baochang Zhang, Jungong Han, Xianbin Cao, Jianzhuang Liu, David S. Doermann:
Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation. AAAI 2019: 8344-8351 - [c190]Li'an Zhuo, Baochang Zhang, Chen Chen, Qixiang Ye, Jianzhuang Liu, David S. Doermann:
Calibrated Stochastic Gradient Descent for Convolutional Neural Networks. AAAI 2019: 9348-9355 - [c189]