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ORCIDDavid S. Doermann
Person information
- affiliation: University at Buffalo, USA
- affiliation (former): University of Maryland, USA
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2020 – today
- 2023
[j58]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)- [j57]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) - 2022
- [j56]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) - [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 - [i36]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) - [i35]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) - [i34]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) - [i33]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) - [i32]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) - [i31]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 - [i30]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) - [i29]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) - [i28]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) - [i27]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) - [i26]Runqi Wang, Baochang Zhang, Li'an Zhuo, Qixiang Ye, David S. Doermann:
Cogradient Descent for Dependable Learning. CoRR abs/2106.10617 (2021) - [i25]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) - [i24]Manan Oza, Sukalpa Chanda, David S. Doermann:
Semantic Text-to-Face GAN -ST^2FG. CoRR abs/2107.10756 (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]Asish Chakrapani GV, Sukalpa Chanda, Umapada Pal, David S. Doermann:
One-Shot Learning-Based Handwritten Word Recognition. ACPR (2) 2019: 210-223 - [c188]Chunlei Liu, Wenrui Ding, Xin Xia, Baochang Zhang, Jiaxin Gu, Jianzhuang Liu, Rongrong Ji, David S. Doermann:
Circulant Binary Convolutional Networks: Enhancing the Performance of 1-Bit DCNNs With Circulant Back Propagation. CVPR 2019: 2691-2699 - [c187]Shaohui Lin, Rongrong Ji, Chenqian Yan, Baochang Zhang, Liujuan Cao, Qixiang Ye, Feiyue Huang, David S. Doermann:
Towards Optimal Structured CNN Pruning via Generative Adversarial Learning. CVPR 2019: 2790-2799 - [c186]Yuchao Li, Shaohui Lin, Baochang Zhang, Jianzhuang Liu, David S. Doermann, Yongjian Wu, Feiyue Huang, Rongrong Ji:
Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression. CVPR 2019: 2800-2809 - [c185]Yi Zhu, Yanzhao Zhou, Huijuan Xu, Qixiang Ye, David S. Doermann, Jianbin Jiao:
Learning Instance Activation Maps for Weakly Supervised Instance Segmentation. CVPR 2019: 3116-3125 - [c184]Xiaolong Jiang, Zehao Xiao, Baochang Zhang, Xiantong Zhen, Xianbin Cao, David S. Doermann, Ling Shao:
Crowd Counting and Density Estimation by Trellis Encoder-Decoder Networks. CVPR 2019: 6133-6142 - [c183]Sukalpa Chanda, Asish Chakrapani GV, Anders Brun, Anders Hast, Umapada Pal, David S. Doermann:
Face Recognition - A One-Shot Learning Perspective. SITIS 2019: 113-119 - [i12]Xiaolong Jiang, Zehao Xiao, Baochang Zhang, Xiantong Zhen, Xianbin Cao, David S. Doermann, Ling Shao:
Crowd Counting and Density Estimation by Trellis Encoder-Decoder Network. CoRR abs/1903.00853 (2019) - [i11]Shaohui Lin, Rongrong Ji, Chenqian Yan, Baochang Zhang, Liujuan Cao, Qixiang Ye, Feiyue Huang, David S. Doermann:
Towards Optimal Structured CNN Pruning via Generative Adversarial Learning. CoRR abs/1903.09291 (2019) - [i10]Chunlei Liu, Wenrui Ding, Xin Xia, Baochang Zhang, Jiaxin Gu, Jianzhuang Liu, Rongrong Ji, David S. Doermann:
Circulant Binary Convolutional Networks: Enhancing the Performance of 1-bit DCNNs with Circulant Back Propagation. CoRR abs/1910.10853 (2019) - [i9]Hanlin Chen, Li'an Zhuo, Baochang Zhang, Xiawu Zheng, Jianzhuang Liu, David S. Doermann, Rongrong Ji:
Binarized Neural Architecture Search. CoRR abs/1911.10862 (2019) - 2018
- [j39]Showmik Bhowmik, Ram Sarkar, Mita Nasipuri, David S. Doermann:
Text and non-text separation in offline document images: a survey. Int. J. Document Anal. Recognit. 21(1-2): 1-20 (2018) - [j38]Shibaprasad Sen, Ankan Bhattacharyya, Pawan Kumar Singh, Ram Sarkar, Kaushik Roy, David S. Doermann:
Application of Structural and Topological Features to Recognize Online Handwritten Bangla Characters. ACM Trans. Asian Low Resour. Lang. Inf. Process. 17(3): 20:1-20:16 (2018) - [i8]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. CoRR abs/1811.12755 (2018) - [i7]Yuchao Li, Shaohui Lin, Baochang Zhang, Jianzhuang Liu, David S. Doermann, Yongjian Wu, Feiyue Huang, Rongrong Ji:
Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression. CoRR abs/1812.04368 (2018) - 2017
- [c182]Sungmin Eum, Hyungtae Lee, Heesung Kwon, David S. Doermann:
IOD-CNN: Integrating object detection networks for event recognition. ICIP 2017: 875-879 - [i6]Sungmin Eum, Hyungtae Lee, Heesung Kwon, David S. Doermann:
IOD-CNN: Integrating Object Detection Networks for Event Recognition. CoRR abs/1703.07431 (2017) - 2016
- [j37]Jingtao Xu, Peng Ye, Qiaohong Li, Haiqing Du, Yong Liu, David S. Doermann:
Blind Image Quality Assessment Based on High Order Statistics Aggregation. IEEE Trans. Image Process. 25(9): 4444-4457 (2016) - [c181]Jingtao Xu, Peng Ye, Qiaohong Li, Yong Liu, David S. Doermann:
No-reference document image quality assessment based on high order image statistics. ICIP 2016: 3289-3293 - [c180]Sungmin Eum, David S. Doermann:
Content selection using frontalness evaluation of multiple frames. ICPR 2016: 3404-3409 - 2015
- [j36]Ankush Roy, Biswajit Halder, Utpal Garain, David S. Doermann:
Machine-assisted authentication of paper currency: an experiment on Indian banknotes. Int. J. Document Anal. Recognit. 18(3): 271-285 (2015) - [j35]Qixiang Ye, David S. Doermann:
Text Detection and Recognition in Imagery: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 37(7): 1480-1500 (2015) - [c179]Sungmin Eum, Hyungtae Lee, David S. Doermann:
JH2R: Joint Homography Estimation for Highlight Removal. BMVC 2015: 49.1-49.12 - [c178]Xianzhi Du, David S. Doermann, Wael Abd-Almageed:
A graphical model approach for matching partial signatures. CVPR 2015: 1465-1472 - [c177]Hongxing Gao, Marçal Rusiñol, Dimosthenis Karatzas, Josep Lladós, Rajiv Jain, David S. Doermann:
Novel line verification for multiple instance focused retrieval in document collections. ICDAR 2015: 481-485 - [c176]Rajiv Jain, David S. Doermann:
Localized document image change detection. ICDAR 2015: 786-790 - [c175]Pawan Kumar Singh, Ram Sarkar, Mita Nasipuri, David S. Doermann:
Word-level script identification for handwritten Indic scripts. ICDAR 2015: 1106-1110 - [c174]Le Kang, Peng Ye, Yi Li, David S. Doermann:
Simultaneous estimation of image quality and distortion via multi-task convolutional neural networks. ICIP 2015: 2791-2795 - [c173]Sravanthi Bondugula, Varun Manjunatha, Larry S. Davis, David S. Doermann:
SHOE: Sibling Hashing with Output Embeddings. ACM Multimedia 2015: 823-826 - [i5]Sravanthi Bondugula, Varun Manjunatha, Larry S. Davis, David S. Doermann:
SHOE: Supervised Hashing with Output Embeddings. CoRR abs/1502.00030 (2015) - 2014
- [j34]Jayant Kumar, Peng Ye, David S. Doermann:
Structural similarity for document image classification and retrieval. Pattern Recognit. Lett. 43: 119-126 (2014) - [c172]Le Kang, Peng Ye, Yi Li, David S. Doermann:
Convolutional Neural Networks for No-Reference Image Quality Assessment. CVPR 2014: 1733-1740 - [c171]Le Kang, Yi Li, David S. Doermann:
Orientation Robust Text Line Detection in Natural Images. CVPR 2014: 4034-4041 - [c170]Peng Ye, Jayant Kumar, David S. Doermann:
Beyond Human Opinion Scores: Blind Image Quality Assessment Based on Synthetic Scores. CVPR 2014: 4241-4248 - [c169]Peng Ye, David S. Doermann:
Active Sampling for Subjective Image Quality Assessment. CVPR 2014: 4249-4256 - [c168]Rajiv Jain, Douglas W. Oard, David S. Doermann:
Scalable ranked retrieval using document images. DRR 2014: 90210K-90210K-15 - [c167]Rajiv Jain, David S. Doermann:
Combining Local Features for Offline Writer Identification. ICFHR 2014: 583-588 - [c166]Jingtao Xu, Peng Ye, Yong Liu, David S. Doermann:
No-reference video quality assessment via feature learning. ICIP 2014: 491-495 - [c165]Qixiang Ye, David S. Doermann:
Robust scene text detection using integrated feature discrimination. ICIP 2014: 1678-1682 - [c164]Le Kang, Peng Ye, Yi Li, David S. Doermann:
A deep learning approach to document image quality assessment. ICIP 2014: 2570-2574 - [c163]Sungmin Eum, David S. Doermann:
Sharpness-aware document image mosaicing using graphcuts. ICIP 2014: 2575-2579 - [c162]Xianzhi Du, David S. Doermann, Wael Abd-Almageed:
Signature Matching Using Supervised Topic Models. ICPR 2014: 327-332 - [c161]