D-Index & Metrics Best Publications
Computer Science
China
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 72 Citations 19,513 494 World Ranking 1028 National Ranking 98

Research.com Recognitions

Awards & Achievements

2023 - Research.com Computer Science in China Leader Award

2019 - IEEE Fellow For contributions to perceptual modeling and processing of visual signals

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Statistics

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 most cited work include:

  • Hierarchical Convolutional Features for Visual Tracking (1192 citations)
  • Cross-scene crowd counting via deep convolutional neural networks (715 citations)
  • Long-term correlation tracking (672 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Artificial intelligence (74.41%)
  • Computer vision (42.64%)
  • Pattern recognition (32.84%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (74.41%)
  • Pattern recognition (32.84%)
  • Computer vision (42.64%)

In recent papers he was focusing on the following fields of study:

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.

Between 2018 and 2021, his most popular works were:

  • Robust Visual Tracking via Hierarchical Convolutional Features (79 citations)
  • Variational Few-Shot Learning (36 citations)
  • Adaptive Region Proposal With Channel Regularization for Robust Object Tracking (32 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Computer vision

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.

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.

Best Publications

Hierarchical Convolutional Features for Visual Tracking

Chao Ma;Jia-Bin Huang;Xiaokang Yang;Ming-Hsuan Yang.
international conference on computer vision (2015)

1780 Citations

Cross-scene crowd counting via deep convolutional neural networks

Cong Zhang;Hongsheng Li;Xiaogang Wang;Xiaokang Yang.
computer vision and pattern recognition (2015)

1036 Citations

Long-term correlation tracking

Chao Ma;Xiaokang Yang;Chongyang Zhang;Ming-Hsuan Yang.
computer vision and pattern recognition (2015)

1035 Citations

Using free energy principle for blind image quality assessment

Ke Gu;Guangtao Zhai;Xiaokang Yang;Wenjun Zhang.
IEEE Transactions on Multimedia (2015)

499 Citations

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)

359 Citations

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)

344 Citations

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)

338 Citations

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)

283 Citations

Crowd Counting via Adversarial Cross-Scale Consistency Pursuit

Zan Shen;Yi Xu;Bingbing Ni;Minsi Wang.
computer vision and pattern recognition (2018)

279 Citations

Unsupervised Deep Learning for Optical Flow Estimation

Zhe Ren;Junchi Yan;Bingbing Ni;Bin Liu.
national conference on artificial intelligence (2017)

254 Citations

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