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Publications

Selected publications

https://dblp.org/pid/03/2079.html or

https://scholar.google.is/citations?user=Y8b1W00AAAAJ&hl=en

 

[C] Min Xie, Yuxi Li, Yabiao Wang, Zekun Luo,  Zhenye Gan,  Zhongyi Sun,  Mingmin Chi*, Chengjie Wang, and Pei Wang, Learning Distinctive Margin toward Active Domain Adaptation, CVPR2022. (与腾讯优图和国台合作,CoRR abs/2203.05738 ）

[C] Huajian Wu and Mingmin Chi*, Hierarchical Signal Fusion Network for Pulsar Detection with Phase-Correlation and Signal Attentions, ICASSP2022.

[C] Bo Peng, Yining Qiu, Dong Wu, Liren He, Mingmin Chi*, A progressive decoupled network for image inpainting, ICME2022.

[J] Bo Peng, Mingmin Chi*, Chao Liu, Non-IID Federated Learning via Random Exchange of Local Feature Maps for Textile IIoT Secure Computing, Science China Information (accepted).

[J] Joseph Kim and Mingmin Chi*, SAFFNet: Self-Attention-Based Feature Fusion Network for Remote Sensing Few-Shot Scene Classification, Remote. Sens. 13(13): 2532 (2021).

[J] Yiqing Qin and Mingmin Chi, RSImageNet: A Universal Deep Semantic Segmentation Lifecycle for Remote Sensing Images. IEEE Access 8: 68254-68267 (2020)

[J]  Yunfeng Zhang and Mingmin Chi, Mask-R-FCN: A Deep Fusion Network for Semantic Segmentation. IEEE Access 8: 155753-155765 (2020).

[C] Penghao Zhou and Mingmin Chi*, “Relation Parsing Neural Network for Human-Object Interaction Detection,” ICCV 2019, Seoul, Korea, Oct. 2019.

[C] Linxiang Lan, Dong Wu, and Mingmin Chi*, “Multi-Temporal Change Detection based on Deep Semantic Segmentation Networks,” Multitemp 2019, Shanghai, China, Aug. 2019.

[J] Pedram Ghamisi, Behnood Rasti, Naoto Yokoya, Qunming Wang, Bernhard Hofle, Lorenzo Bruzzone, Francesca Bovolo, Mingmin Chi, Katharina Anders, Richard Gloaguen, Peter M. Atkinson, Jon Atli Benediktsson, “Multisource and Multitemporal Data Fusion in Remote Sensing,” IEEE Geoscience and Remote Sensing Magazine, Vol. 7, No.1, pp. 6-39, Mar. 2019.

[C] Huan Zhou, Yang Hu, Jinshu Su, Mingmin Chi, Cees de Laat, Zhiming Zhao, “Empowering Dynamic Task-Based Applications with Agile Virtual Infrastructure Programmability,” IEEE CLOUD 2018: 484-491.

Zhongsheng Li, Qiuhong Li, Yimin Liu, Wei Wang, Fengbin Qi, Mingmin Chi, Yitong Wang, “Modeling and Evaluating MID1 ICAL Pipeline on Spark,” DASFAA (2) 2018: 825-828. 

[C] Xuan Liu, Mingmin Chi, Yunfeng Zhang, Yiqing Qin, “Classifying High Resolution Remote Sensing Images by Fine-Tuned VGG Deep Networks,” IGARSS 2018: 7137-7140.

[C] Yiqing Qin, Mingmin Chi, Xuan Liu, Yunfeng Zhang, Yijian Zeng, Zhiming Zhao, “Classification of High Resolution Urban Remote Sensing Images Using Deep Networks by Integration of Social Media Photos,” IGARSS 2018: 7243-7246.

[J] Dong Wu and Mingmin Chi, “Long Short-Term Memory with Quadratic Connections in Recursive Neural Networks for Representing Compositional Semantics,” IEEE Access, Vol. 5, pp. 16077-16083, Jan. 2017. 

[J] Sicong Liu, Mingmin Chi, Yangxiu Zou, Alim Samat, Jon Atli Benediktsson, Antonio Plaza, “Oil Spill Detection via Multitemporal Optical Remote Sensing Images: A Change Detection Perspective,” IEEE Geosci. Remote Sensing Lett. 14(3),pp. 324-328,2017.

[J] Mingmin Chi, Zhongyi Sun, Yiqing Qin, Jinsheng Shen, Jon Atli Benediktsson, “A Novel Methodology to Label Urban Remote Sensing Images Based on Location-Based Social Media Photos,” Proceedings of the IEEE, Vol. 105, No. 10, pp. 1926-1936,  2017.

[C] Fengyu Li, Mingmin Chi, Dong Wu, Junyu Niu, “Hierarchical Parameter Sharing in Recursive Neural Networks with Long Short-Term Memory,” ICONIP (2) 2017: 582-592.

[J] Mingmin Chi, Antonio Plaza, Jon Atli Benediktsson, Jingsheng Shen, Zhongyi Sun, Fengke Chen, and Yangyong Zhu, “Big Data for Remote Sensing: Challenges and Opportunities,” Proceedings of the IEEE, Vol. 104, No.11, pp.2207-2219, Nov. 2016.

[J] Zhongyi Sun, Mingmin Chi, Jon Atli Benediktsson, “Computational Efficiency Active Learning for classification of hyperspectral images,” IGARSS 2016: 5138-5140. 

[J] Sicong Liu, Mingmin Chi, Yangxiu Zou, Alim Samat, “A multitemporal change detection solution to oil spill monitoring,” IGARSS 2016: 7718-7721.


Before 2016

Book Chapters & Journal Articles

  • Mingmin Chi, Antonio Plaza, Jon Atli Benediktsson, Bing Zhang, and Boming Huang，“Foreword to the Special Issue on Big Data in Remote Sensing”，IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (IEEE JSTARS), Vol.8. No. 10, pp. 4607-4609, 2015.

  • Jiangfeng Bao, Mingmin Chi, and Jon Atli Benediktsson, “Spectral Derivative Features for Classification of Hyperspectral Remote Sensing Images:  Experimental Evaluation,  ” IEEE Journal of Selected Topics in Applied Earth Observations and RemoteSensing, Vol. 6, No.2, pp. 594 – 601, 2013.

  • Waske, B., Mingmin Chi, Benediktsson, J., A., van der Linden, S., Koetz, B., “Algorithms  and applications for land cover classification – a review, ”In: Li, D., Shan,  J., Gong, J. (Eds.), Geospatial Technology for Earth Observation, pp. 203-233, Springer, 2009.

  • Mingmin Chi,   Qian Kun, Jon A. Benediktsson and Rui Feng, “Ensemble   Classification Algorithm for Hyperspectral Remote  Sensing Data,” IEEE Geoscience and Remote Sensing Letters, No. 3, pp. 762-766, Oct. 2009.

  • Mingmin  Chi, Rui Feng, and Lorenzo Bruzzone, “Classification of hyperspectral remote-sensing data with primal SVM for  small-sized training dataset problem, ” Advances in  Space Research, vol. 41, no. 11, pp. 1793-1799, 2008.

  • Mingmin Chi and Lorenzo Bruzzone, “Semi-Supervised Classification of Hyperspectral Images by SVMs Optimized in the Primal,” IEEE Transaction on Geoscience and Remote Sensing, vol. 45, no. 6, pp. 1870-1880, Jun. 2007.

  • Lorenzo Bruzzone, Mingmin Chi and Mattia Marconcini, “”A novel transductive SVM for semisupervised classification of remote sensing images,” IEEE Transaction on Geoscience and Remote Sensing. vol. 44, no. 11, pp. 3363-3373, Nov. 2006.

  • Mingmin Chi and Lorenzo Bruzzone, “An ensemble-driven k-NN approach to ill-posed classification problems,” Pattern Recognition Letters, vol. 27, no. 4, pp. 301-307, 2005.

  • Mingmin Chi and Lorenzo Bruzzone, “A semilabeled-sample-driven bagging technique for ill-posed classification problems,”IEEE Geoscience and Remote Sensing Letters, vol. 2, no. 1, pp. 69-73, January 2005.

Selected Conferences:

  • Mingmin Chi, Jiangfeng Bao, Yangxiu Zou. Jon Atli Benediktsson, “Deep Neural Networks for Remote Sensing Image Classification”, IGARSS’13, Melbourne, Australian, July, 2013.

  • Mingmin Chi, Jun Liu, Huijun He, Jiangfeng Bao, Yangyong Zhu, “Construction of Chinese A-shares Network Using Latent Dirichlet Allocation, ” IEEE/WIC/ACM Web Intelligence 2012 (WI’12), Maucau, China, Dec. 2012.

  • Huijun He, Mingmin Chi, Wenqiang Zhang, “Fuseptron: a Kernel Fused Perceptron for Large-Scale Data Classification, ” BigMine-2012, KDD’12, Beijing, China, Aug., 2012.

  • Mingmin Chi, Jiangfeng Bao,  Xintao Chen, Jon Atli Benediktsson, “Input-Ouput-Consistent Domain Adaptation Algorithm for Remote Sensing Data Classification, ” IGARSS’12 ,Munich, Germany, July, 2012.

  • Jiangfeng Bao, Mingmin Chi, Jon Atli Benediktsson, “When Spectral Derivative Feature Working for the Supervised Classification of Remote Sensing Data: an Experimental Evaluation, ” WHISPERS’12 , Shanghai, China, June, 2012.

  • Mingmin Chi, Huijun He and Wenqiang Zhang, ” Nonlinear Online Classification  Algorithm with Probability Margin, ” Journal of Machine Learning Research -Proceedings Track 20: 33-46 (2011).

  • Mingmin Chi, Jun Liu, Jiangfeng Bao, Jon Atli Benediktsson, “Scalable  semi-supervised classification of hyperspectral remote sensing data with spectral and spatial information, ” IEEE Int. Geoscience and Remote Sensing Symposium (IGARSS’11),  Jul. 24-29, Vancouver, Canada.

  • Mingmin Chi, Xisheng He and Shipeng Yu, “Mixture Model Label  Propagation,” Proceedings of the 19th ACM international conference on Information and knowledge management (CIKM2010), pp. 1889–1892, Toronto, Canada, Oct. 2010.

  • Mingmin Chi, Youdong Miao, Youze Tang, Jon Atli Benediktsson, Xuanjing Huang, “Hierarchical Ensemble   Support Cluster Machine,” MCS 2009: 252-261.

  • Mingmin Chi, Peiwu Zhang, Yingbin Zhao, Rui Feng, Xiangyang Xue, “Web Image Retrieval Reranking with Multi-view Clustering, ” WWW 2009: 1189-1190.

  • Mingmin  Chi, Kun Qian, Jón Atli Benediktsson, “Cluster-based Ensemble  Classification for Hyperspectral Remote Sensing Images,” IEEE Int. Geoscience and Remote Sensing Symposium  (IGARSS’08), Boston, U.S.A., July, 2008.

  • Qing Wang, Liang Zhang,  Mingmin Chi, Jiankui Guo, “MTForest: Ensemble Decision Trees based on  Multi-Task Learning,” European Conference on Artificial  Intelligence (ECAI 2008), Patras, Greece,  July, 2008.

  • Wei Zhang, Xiangyang Xue, Zichen Sun, Yuefei Guo, Mingmin Chi, and Hong Lu, “Efficient Feature Extraction for Image Classification,” 11th IEEE International Conference on Computer Vision (ICCV 2007), Rio de Janeiro, Brazil, Oct. 2007.

  • Ilya Zaihrayeu, Lei Sun, Fausto Giunchiglia, Wei Pan, Qi Ju, Mingmin Chi,
    and Xuanjing Huang, “From Web Directories to Ontologies: Natural Language Processing Challenges,” International Semantic Web Conference+Asian Semantic Web Conference (ISWC+ASWC 2007), Busan, Korea, Nov. 2007.

  • Mingmin Chi and Lorenzo Bruzzone, “Classification of Hyperspectral Remote Sensing Data with Primal Semi-Supervised SVMs,” IEEE Int. Geoscience and Remote Sensing Symposium (IGARSS’07), Barcelona, Spain, July 2007.

  • Bin Li, Mingmin Chi, Jianpin Fan and Xiangyang Xue, “Support Cluster Machine,” 24th International Conference on Machine Learning (ICML’07), Corvallis, USA, June 2007.

  • Olivier Chapelle, Mingmin Chi and Alexander Zien, “A Continuation Method for Semi-Supervised SVMs,” 23rd International Conference on Machine Learning (ICML’06), Pittsburgh, USA, June 2006.

PhD Theses

  • Mingmin Chi, Advanced Semi-Supervised Techniques for the Classification of Remote Sensing Data, Mar. 2006.


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