2023 - Research.com Computer Science in China Leader Award
2019 - IEEE Fellow For contributions to perceptual modeling and processing of visual signals
His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Image quality and Machine learning. Artificial intelligence connects with themes related to Metric in his study. His study connects Video quality and Computer vision.
His Pattern recognition research is multidisciplinary, relying on both Matching, Regularization, Optical flow estimation and Context model. In his research on the topic of Image quality, Computational complexity theory, Adaptive algorithm, Coding, Discrete wavelet transform and Clipping is strongly related with Transform coding. The study incorporates disciplines such as Training set and Data mining in addition to Machine learning.
His primary areas of investigation include Artificial intelligence, Computer vision, Pattern recognition, Image quality and Algorithm. His Artificial intelligence research includes elements of Machine learning and Metric. The Computer vision study combines topics in areas such as Visualization and Robustness.
His biological study spans a wide range of topics, including Artificial neural network, Image restoration and Feature. His Image quality research incorporates elements of Transform coding and Structural similarity. His Mathematical optimization research extends to Algorithm, which is thematically connected.
His primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Convolutional neural network and Artificial neural network. Artificial intelligence is closely attributed to Machine learning in his research. His work carried out in the field of Pattern recognition brings together such families of science as Recurrent neural network, Representation, Color depth and Benchmark.
In general Computer vision, his work in Object detection is often linked to Haze linking many areas of study. His Convolutional neural network research includes themes of Algorithm and Decoding methods. His work deals with themes such as Visualization, Iterative reconstruction, Support vector machine and Feature, which intersect with Feature extraction.
His primary scientific interests are in Artificial intelligence, Pattern recognition, Image quality, Computer vision and Feature extraction. His Artificial intelligence study frequently draws parallels with other fields, such as Machine learning. In his study, which falls under the umbrella issue of Pattern recognition, Object detection, Minimum bounding box and Task is strongly linked to Region of interest.
Xiaokang Yang has included themes like Database, Metric, Face, Quality assessment and Bridge in his Image quality study. In the field of Computer vision, his study on Aerial image overlaps with subjects such as Haze. His Feature extraction study combines topics from a wide range of disciplines, such as Cognitive neuroscience of visual object recognition, Perception and Haar wavelet.
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Hierarchical Convolutional Features for Visual Tracking
Chao Ma;Jia-Bin Huang;Xiaokang Yang;Ming-Hsuan Yang.
international conference on computer vision (2015)
Cross-scene crowd counting via deep convolutional neural networks
Cong Zhang;Hongsheng Li;Xiaogang Wang;Xiaokang Yang.
computer vision and pattern recognition (2015)
Long-term correlation tracking
Chao Ma;Xiaokang Yang;Chongyang Zhang;Ming-Hsuan Yang.
computer vision and pattern recognition (2015)
Using free energy principle for blind image quality assessment
Ke Gu;Guangtao Zhai;Xiaokang Yang;Wenjun Zhang.
IEEE Transactions on Multimedia (2015)
Just noticeable distortion model and its applications in video coding
Xiaokang Yang;W. S. Ling;Zhongkang Lu;Ee Ping Ong.
Signal Processing-image Communication (2005)
Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking
Jun Yu;Xiaokang Yang;Fei Gao;Dacheng Tao.
IEEE Transactions on Systems, Man, and Cybernetics (2017)
Analytic solution of a two-dimensional hydrogen atom. I. Nonrelativistic theory
X. L. Yang;S. H. Guo;F. T. Chan;K. W. Wong.
Physical Review A (1991)
Learning a no-reference quality metric for single-image super-resolution
Chao Ma;Chao Ma;Chih Yuan Yang;Xiaokang Yang;Ming Hsuan Yang.
Computer Vision and Image Understanding (2017)
Crowd Counting via Adversarial Cross-Scale Consistency Pursuit
Zan Shen;Yi Xu;Bingbing Ni;Minsi Wang.
computer vision and pattern recognition (2018)
Unsupervised Deep Learning for Optical Flow Estimation
Zhe Ren;Junchi Yan;Bingbing Ni;Bin Liu.
national conference on artificial intelligence (2017)
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