Publications

Recent Papers (2014~)


[1]  Xu-Cheng Yin, Wei-Yi Pei, Jun Zhang, and Hong-Wei Hao, “Multi-orientation scene text detection with adaptive clustering,” IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), vol. 37, no. 9, pp. 1930-1937, 2015. <Online Databset> <Paper Link> (Our multi-orientation scene text detection technology has the best performance on available public datasets. 2017 SCI Impact Factor: 8.329.)

 

[2] Xu-Cheng Yin, Xuwang Yin, Kaizhu Huang, and Hong-Wei Hao, “Robust text detection in natural scene images”, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 36, no. 5, pp. 970-983, 2014. <Paper Link (IEEE Xplore)> <Online Demos>  (Our published technology ("USTB_TexStar") won the 1st place of both "Text Localization in Real Scenes" and "Text Localization in Born-Digital Images (Web and Email)" in ICDAR 2013 Robust Reading Competition; our technology ("Yin et al.") also won the 1st place in ICDAR 2013 Multi-Script Robust Reading Competition. This paper is a highly cited paper from ESI (Essential Science Indicators) as of Nov/Dec 2015. 2017 SCI Impact Factor: 8.329.)

 

[3] Chun Yang, Xu-Cheng Yin*, Wei-Yi Pei, Shu Tian, Ze-Yu Zuo, Chao Zhu and Junchi Yan, "Tracking based multi-orientation scene text detection: A unified framework with dynamic programming," IEEE Trans. Image Processing (TIP), vol. 26, no. 7, pp. 3235-3248, 2017. <Paper Link> (2017 SCI Impact Factor: 4.828.)

 

[4] Xu-Cheng Yin, Ze-Yu Zuo, Shu Tian, and Cheng-Lin Liu, "Text detection, tracking and recognition in video: A comprehensive survey," IEEE Trans. Image Processing (TIP), vol. 25, no. 6, pp. 2752-2773, 2016. <Paper Link> (2017 SCI Impact Factor: 4.828.)

 

[5] Ya Su, Xinbo Gao, and Xu-Cheng Yin, "Fast alignment for sparse representation based face recognition," Pattern Recognition, vol. 68, pp. 211-222, 2017. <Paper Link> (2017 SCI Impact Factor: 4.582.)

 

[6] Xu-Cheng Yin, Kaizhu Huang, Chun Yang, and Hong-Wei Hao, “Convex ensemble learning with sparsity and diversity,” Information Fusion, vol. 20, pp. 49-59, 2014. <Paper Link> (2017 SCI Impact Factor: 5.667.)

 

[7] Bo-Wen Zhang, Xu-Cheng Yin*, and Fang Zhou, “A generic pseudo relevance feedback framework with heterogeneous social information,” Information Sciences, vol. 367-368, pp. 909-926, 2016. <Paper Link> (Our proposed technology (USTB-PRIR”) won the 1st place of CLEF 2016 Social Book Search Suggestion Task.) (2017 SCI Impact Factor: 4.832.)

 

[8] Xu-Cheng Yin, Kaizhu Huang, and Hong-Wei Hao, “DE2: Dynamic ensemble of ensembles for learning nonstationary data,” Neurocomputing, vol. 165, pp. 14-22, 2015. <Paper Link> (2017 SCI Impact Factor: 3.317.)

 

[9] Xu-Cheng Yin, Kaizhu Huang, and Hong-Wei Hao, “A novel classifier ensemble method with sparsity and diversity,” Neurocomputing, vol. 134, pp. 214-221, 2014. <Paper Link> (2017 SCI Impact Factor: 3.317.)

 

[10] Xu-Cheng Yin, Bo-Wen Zhang, Xiao-Ping Cui, Jiao Qu, Bin Geng, Fang Zhou, Li Song, and Hong-Wei Hao, "IsART: A Generic Framework for Searching Books with Social Informaiton," PLoS ONE, vol. 11, no. 2, pp. e0148479, 2016. (Our proposed technology won the top place of CLEFT/INEX 2014 Social Book Search Suggestion Task.) <Paper Link> (2017 SCI Impact Factor: 2.806.)

 

[11] Xu-Cheng Yin, Chun Yang, Wei-Yi Pei, Haixia Man, Jun Zhang, Erik Learned-Miller, and Hong Yu, "DeTEXT: A database for evaluating text extraction from biomedical literature figures," PLoS ONE, vol. 10, no. 5, pp. e0126200, 2015. <Online Databset> <Paper Link> (2017 SCI Impact Factor: 2.806.)

 

[12] Kaizhu Huang, Rui Zhang, and Xu-Cheng Yin, “Imbalance Learning locally and Globally,” Neural Processing Letters, vol. 41, no. 3, pp. 311-323, 2015. (2017 SCI Impact Factor: 1.620.)

 

[13] Shu Tian, Xu-Cheng Yin*, Zhi-Bin Wang, and Hong-Wei Hao, "VeBIRD: A VidEo-Based Intelligent Recognition and Decision system for the phacoemulsification cataract surgery," Computational and Mathematical Methods in Medicine, 202934:1-202934:11, 2015. (2017 SCI Impact Factor: 0.937.)

 

[14] Yan Yan, Xu-Cheng Yin*, Sujian Li, Mingyuan Yang, Hong-Wei Hao, "Learning document semantic representation with hybrid deep belief network," Computational Intelligence and Neuroscience, 650527:1-650527:9, 2015. (2017 SCI Impact Factor: 1.215.)

 

[15] Khalid Iqbal, Xu-Cheng Yin*, Hong-Wei Hao, Qazi Ilyas, and Xuwang Yin, “A central tendency-based privacy preserving model for sensitive XML association rules using Bayesian networks,” Intelligent Data Analysis, vol. 18, no. 2, pp. 281-303, 2014. <Paper Link> (2017 SCI Impact Factor: 0.810.)

 


[16] Bo-Wen Zhang, Xu-Cheng Yin*, Fang Zhou*, and Jianlin Jin, "Building your own reading list anytime via embedding relevance, quality, timeliness and diversity," Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’17), 2017.

 

[17] Wei-Yi Pei, Chun Yang, Lih-Jen Kau, and Xu-Cheng Yin*, "Multi-orientation scene text detection with multi-information fusion," Proceedings of International Conference on Pattern Recognition (ICPR'16), 2016.

 

[18] Zong-Heng Xing, Fang Zhou, Shu Tian, and Xu-Cheng Yin*, "Robust segmentation for video captions with complex backgrounds," Processing of 7th Chinese Conference on Pattern Recognition (CCPR'16), 2016. <Paper Link> (Best Student Paper of CCPR'16)

 

[19] Yan Yan, Xu-Cheng Yin*, Chun Yang, Bo-Wen Zhang, and Hong-Wei Hao, "Multi-label ranking with LSTM^2 for document classification," Processing of 7th Chinese Conference on Pattern Recognition (CCPR'16), 2016.

 

[20] Song-Lu Chen, Chun Yang, Chao Zhu, and Xu-Cheng Yin*, "Bloody image classification with global and local features," Processing of 7th Chinese Conference on Pattern Recognition (CCPR'16), 2016. <Online Demo>

 

[21] Shu Tian+, Wei-Yi Pei+, Ze-Yu Zuo, and Xu-Cheng Yin*, "Scene text detection in video by learning locally and globally," Proceedings of 25th International Joint Conference on Artificial Intelligence (IJCAI'16), 2016. <Paper Link> (Our technology won the 1st Place of "(Text in Videos) Video Text Detection" in ICDAR 2015 Robust Reading Competition.)

 

[22] Junchi Yan, Xu-Cheng Yin, Weiyao Lin, Cheng Deng, Hongyuan Zha, and Xiaokang Yang, "A short survey of recent advances in graph matching," Proceedings of ACM International Conference on Multimedia Retrieval (ICMR'16), 2016.

 

[23] Shao-Hui Feng, Bo-Wen Zhang*, Xu-Cheng Yin*, etc., USTB at Social Book Search 2016 Suggestion Task: Active books set and re-ranking, CLEF (Working Notes), 2016.

 

[24] Zhijuan Zhang, Tiantian Liu, Bo-Wen Zhang, Yan Li, Chun Hua Zhao, Shao-Hui Feng, Xu-Cheng Yin*, and Fang Zhou, A generic retrieval system for biomedical literatures: USTB at BioASQ2015 Question Answering Task,CLEF (Working Notes), 2015. (Our technology won several batches of 2015 BioASQ Challenge Task 3b: Biomedical Semantic QA.)

 

[25] Chunhua Zhao, Fang Zhou, Bo-Wen Zhang, Xu-Cheng Yin*, Ming Hao, Zhijuan Zhang, and Tiantian Liu, USTB at Social Book Search 2015 Suggestion Task: Metadata Expansion and Reranking, CLEF (Working Notes), 2015.

 

[26] Ze-Yu Zuo, Shu Tian, Wei-Yi Pei, and Xu-Cheng Yin*, "Multi-strategy tracking based text detection in scene videos," Proceedings of 13th International Conference on Document Analysis and Recognition (ICDAR'15), 2015.

 

[27] Bo-Wen Zhang, Xu-Cheng Yin*, Xiao-Ping Cui, Jiao Qu, Bin Geng, Fang Zhou, Li Song, and Hong-Wei Hao, “Social book search reranking with generalized content-based filtering”, Proceedings of ACM International Conference on Information and Knowledge Management (CIKM'14), 2014. <Paper Link> (Our proposed technology (USTB) won the 1st place of CLEF/INEX 2014 Social Book Search Suggestion Task.)

 

[28] Xu-Cheng Yin, Chun Yang, Wei-Yi Pei, and Hong-Wei Hao, “Shallow classification or deep learning: An experimental study,” Proceedings of International Conference on Pattern Recognition (ICPR'14), 2014.

 

[29] Chun Yang, Xu-Cheng Yin*, and Hong-Wei Hao, “Diversity-based ensemble with sample weight learning,” Proceedings of International Conference on Pattern Recognition (ICPR'14), 2014.


[30] Khalid Iqbal, Xu-Cheng Yin*, Hong-Wei Hao, Sohail Asghar, and Hazrat Ali, “Bayesian network scores based text localization in scene images,” Proceedings of International Joint Conference on Neural Networks (IJCNN'14), 2014.

 

[31] Chun Yang, Xu-Cheng Yin*, and Kaizhu Huang, "Text categorization with diversity Random Forests," Proceedings of International Conference on Neural Information Processing (ICONIP’14), 2014.

 

[32] Bin Geng, Fang Zhou, Jiao Qu, Bo-Wen Zhang, Xiao-Ping Cui, and Xu-Cheng Yin*, "Social book search with pseudo-relevance feedback," Proceedings of International Conference on Neural Information Processing (ICONIP’14), 2014.

 

 

Latest Accepted Papers

 

[1] Shu Tian, Xu-Cheng Yin*,  Ya Su, and Hong-Wei Hao, "A unified framework for tracking based text detection and recognition from web videos," IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), accepted and online, 2017. <Paper Link> (2017 SCI Impact Factor: 8.329.)

 

[2] Ahmad Shaheryar, Xu-Cheng Yin*, and Hong-Wei Hao, "Selection of optimal denoising-based regularization hyper-parameters for performance improvement in a sensor validation model," Artificial Intelligence Review, accepted and online, 2017. (2017 SCI Impact Factor: 2.627.)

 

[3] Bo-Wen Zhang, and Xu-Cheng Yin*, "SSDM^2: A two-stage semantic sequential dependence model framework for biomedical question answering," Cognitive Computation, accepted, 2017. (2017 SCI Impact Factor: 3.441.)

 

[4] Yan Yan, Ying Wang, Chen-Chao Gao, Bo-Wen Zhang, Chun Yang, and Xu-Cheng Yin, "LSTM^2: Multi-label ranking for document classification," Neural Processing Letters, accepted and online, 2017. (2017 SCI Impact Factor: 1.620.)

 

 

Latest Submitted (Journal) Papers

 

[1] Xu-Cheng Yin, Chun Yang, and Hong-Wei Hao,  “Learning to diversify via weighted kernels for classifier ensemble,” submitted to IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), 2014. <Source Codes and Dataset>

 

[2] Shu Tian, Xu-Cheng Yin*, Zong-Heng Xing, Fang Zhou, etc al., "Tracking based text segmentation for video captions with complex backgrounds," submitted to IEEE Trans. Image Processing (TIP), 2017.

 

[3] Chun Yang, and Xu-Cheng Yin*, "Diversity-based Random Forests via sample weight learning," submitted to IEEE Trans. Cybernetics (TC), 2017.

 


|Powered By Google Sites