2021 - ACM Fellow For contributions to visual tracking, face processing, and low-level vision
2019 - IEEE Fellow For contributions to object tracking and face recognition
2007 - ACM Senior Member
His primary scientific interests are in Artificial intelligence, Pattern recognition, Computer vision, Video tracking and Eye tracking. His studies in Robustness, Feature extraction, Discriminative model, Artificial neural network and Active appearance model are all subfields of Artificial intelligence research. His Pattern recognition research includes elements of Contextual image classification, Object detection, Facial recognition system and Iterative reconstruction.
As a part of the same scientific study, Ming-Hsuan Yang usually deals with the Computer vision, concentrating on Benchmark and frequently concerns with Machine learning. His biological study spans a wide range of topics, including Histogram, Tracking system and Motion blur. The study incorporates disciplines such as Visualization, Particle filter, Correlation and Subspace topology in addition to Eye tracking.
Ming-Hsuan Yang mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Convolutional neural network and Image. His study in Artificial intelligence focuses on Segmentation, Object, Video tracking, Feature and Discriminative model. Ming-Hsuan Yang usually deals with Pattern recognition and limits it to topics linked to Eye tracking and Visualization.
His work on Computer vision is being expanded to include thematically relevant topics such as Benchmark. Ming-Hsuan Yang regularly ties together related areas like Optical flow in his Convolutional neural network studies. The Deblurring study combines topics in areas such as Kernel density estimation, Kernel and Motion blur.
Ming-Hsuan Yang mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Convolutional neural network and Feature. His study involves Object, Benchmark, Segmentation, Image and Regularization, a branch of Artificial intelligence. Ming-Hsuan Yang interconnects Pixel, Semantics and Object detection in the investigation of issues within Pattern recognition.
His work on Image warping, Optical flow and Image editing as part of his general Computer vision study is frequently connected to Focus, thereby bridging the divide between different branches of science. His Convolutional neural network research is multidisciplinary, incorporating elements of Real image, Deblurring, Face and Feature extraction. His Feature study combines topics from a wide range of disciplines, such as Image synthesis, Content creation and Selection.
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Convolutional neural network, Feature and Computer vision. His Machine learning research extends to Artificial intelligence, which is thematically connected. His Pattern recognition research incorporates themes from Semantics, Image restoration and Object detection.
His Convolutional neural network study integrates concerns from other disciplines, such as Channel, Pixel, Real image and Artificial neural network. Ming-Hsuan Yang focuses mostly in the field of Feature, narrowing it down to matters related to Embedding and, in some cases, Linear classifier, Closing and Feature learning. He works mostly in the field of Computer vision, limiting it down to topics relating to Content creation and, in certain cases, Translation.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Detecting faces in images: a survey
Ming-Hsuan Yang;D.J. Kriegman;N. Ahuja.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2002)
Online Object Tracking: A Benchmark
Yi Wu;Jongwoo Lim;Ming-Hsuan Yang.
computer vision and pattern recognition (2013)
Incremental Learning for Robust Visual Tracking
David A. Ross;Jongwoo Lim;Ruei-Sung Lin;Ming-Hsuan Yang.
International Journal of Computer Vision (2008)
Robust Object Tracking with Online Multiple Instance Learning
B. Babenko;Ming-Hsuan Yang;S. Belongie.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2011)
Visual tracking with online Multiple Instance Learning
Boris Babenko;Ming-Hsuan Yang;Serge Belongie.
computer vision and pattern recognition (2009)
Fast Compressive Tracking
Kaihua Zhang;Lei Zhang;Ming-Hsuan Yang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2014)
Object Tracking Benchmark
Yi Wu;Jongwoo Lim;Ming-Hsuan Yang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2015)
Saliency Detection via Graph-Based Manifold Ranking
Chuan Yang;Lihe Zhang;Huchuan Lu;Xiang Ruan.
computer vision and pattern recognition (2013)
Real-time compressive tracking
Kaihua Zhang;Lei Zhang;Ming-Hsuan Yang.
european conference on computer vision (2012)
Visual tracking via adaptive structural local sparse appearance model
Xu Jia;Huchuan Lu;Ming-Hsuan Yang.
computer vision and pattern recognition (2012)
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