2019 - ACM Fellow For contributions to representation learning and its applications
2017 - Australian Laureate Fellow
2017 - Fellow of the American Association for the Advancement of Science (AAAS)
2016 - Member of Academia Europaea
2013 - SPIE Fellow
2012 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to pattern recognition and image understanding
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Machine learning. Artificial intelligence is a component of his Feature, Discriminative model, Dimensionality reduction, Contextual image classification and Robustness studies. His work is dedicated to discovering how Pattern recognition, Subspace topology are connected with Theoretical computer science and other disciplines.
Dacheng Tao has included themes like Artificial neural network, Representation, Feature vector, Facial recognition system and Neural coding in his Feature extraction study. Within one scientific family, he focuses on topics pertaining to Image retrieval under Machine learning, and may sometimes address concerns connected to Graph. In his study, Algorithm is strongly linked to Convolutional neural network, which falls under the umbrella field of Deep learning.
Dacheng Tao focuses on Artificial intelligence, Pattern recognition, Machine learning, Computer vision and Feature extraction. His study in Discriminative model, Image, Feature, Robustness and Subspace topology is carried out as part of his studies in Artificial intelligence. His Pattern recognition research incorporates themes from Contextual image classification, Facial recognition system and Cluster analysis.
His Machine learning research integrates issues from Training set, Image retrieval, Metric and Benchmark. His is doing research in Image processing, Image quality and Pixel, both of which are found in Computer vision. His work in Feature extraction is not limited to one particular discipline; it also encompasses Visualization.
Dacheng Tao mostly deals with Artificial intelligence, Machine learning, Pattern recognition, Deep learning and Artificial neural network. Dacheng Tao focuses mostly in the field of Artificial intelligence, narrowing it down to topics relating to Computer vision and, in certain cases, Frame. His research on Machine learning often connects related areas such as Inference.
His work in Pattern recognition addresses subjects such as Code, which are connected to disciplines such as Object. He works mostly in the field of Artificial neural network, limiting it down to topics relating to Algorithm and, in certain cases, Kernel. The study incorporates disciplines such as Multi-task learning, Inpainting, Data mining and Benchmark in addition to Feature.
His primary scientific interests are in Artificial intelligence, Artificial neural network, Pattern recognition, Deep learning and Machine learning. His research ties Computer vision and Artificial intelligence together. His work deals with themes such as Algorithm, Quantum neural network and Topology, which intersect with Artificial neural network.
His Pattern recognition research includes themes of Subspace topology, Data point, Texture and Cluster analysis. His Deep learning research is multidisciplinary, relying on both Variety, Field, Scalability and Data science. His Machine learning research integrates issues from Data modeling and Upper and lower bounds.
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General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
Dacheng Tao;Xuelong Li;Xindong Wu;S.J. Maybank.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)
Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval
Dacheng Tao;Xiaoou Tang;Xuelong Li;Xindong Wu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)
DehazeNet: An End-to-End System for Single Image Haze Removal
Bolun Cai;Xiangmin Xu;Kui Jia;Chunmei Qing.
IEEE Transactions on Image Processing (2016)
A Survey on Multi-view Learning
Chang Xu;Dacheng Tao;Chao Xu.
arXiv: Learning (2013)
A survey of graph edit distance
Xinbo Gao;Bing Xiao;Dacheng Tao;Xuelong Li.
Pattern Analysis and Applications (2010)
Geometric Mean for Subspace Selection
Dacheng Tao;Xuelong Li;Xindong Wu;S.J. Maybank.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)
GoDec: Randomized Low-rank & Sparse Matrix Decomposition in Noisy Case
Tianyi Zhou;Dacheng Tao.
international conference on machine learning (2011)
MUlti-Store Tracker (MUSTer): A cognitive psychology inspired approach to object tracking
Zhibin Hong;Zhe Chen;Chaohui Wang;Xue Mei.
computer vision and pattern recognition (2015)
Beyond streams and graphs: dynamic tensor analysis
Jimeng Sun;Dacheng Tao;Christos Faloutsos.
knowledge discovery and data mining (2006)
NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results
Radu Timofte;Eirikur Agustsson;Luc Van Gool;Ming-Hsuan Yang.
computer vision and pattern recognition (2017)
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