H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 37 Citations 7,524 194 World Ranking 5234 National Ranking 144

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Operating system

Wanqing Li mainly focuses on Artificial intelligence, Pattern recognition, Discriminative model, Computer vision and Convolutional neural network. His Feature extraction, Artificial neural network and Unsupervised learning study in the realm of Artificial intelligence connects with subjects such as Action recognition. His Pattern recognition research focuses on subjects like Joint, which are linked to Linear subspace.

His Discriminative model research includes elements of Neocognitron and Gesture. His work deals with themes such as Graph theory, Graph and Hidden Markov model, which intersect with Computer vision. His research investigates the connection between Convolutional neural network and topics such as RGB color model that intersect with problems in Deep learning, Color space and Kernel.

His most cited work include:

  • Action recognition based on a bag of 3D points (1050 citations)
  • The genome of the choanoflagellate Monosiga brevicollis and the origin of metazoans. (856 citations)
  • Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks (250 citations)

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

Wanqing Li spends much of his time researching Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Convolutional neural network. Wanqing Li undertakes multidisciplinary investigations into Artificial intelligence and Action recognition in his work. His work in Pattern recognition covers topics such as Object detection which are related to areas like Template matching.

His Computer graphics research extends to Computer vision, which is thematically connected. His studies in Convolutional neural network integrate themes in fields like Recurrent neural network, Deep learning and Pooling. The RGB color model study combines topics in areas such as Modality and Skeleton.

He most often published in these fields:

  • Artificial intelligence (72.89%)
  • Pattern recognition (46.52%)
  • Computer vision (34.43%)

What were the highlights of his more recent work (between 2016-2021)?

  • Artificial intelligence (72.89%)
  • Pattern recognition (46.52%)
  • Convolutional neural network (13.55%)

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

His primary areas of investigation include Artificial intelligence, Pattern recognition, Convolutional neural network, RGB color model and Feature extraction. As a part of the same scientific family, Wanqing Li mostly works in the field of Artificial intelligence, focusing on Computer vision and, on occasion, Neocognitron. His work on Discriminative model as part of his general Pattern recognition study is frequently connected to Scale, thereby bridging the divide between different branches of science.

His research in Convolutional neural network intersects with topics in Representation, Pooling and Encoding. His RGB color model research is multidisciplinary, incorporating perspectives in Modality and Skeleton. Wanqing Li has included themes like Convolution and Feature in his Feature extraction study.

Between 2016 and 2021, his most popular works were:

  • Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN (213 citations)
  • Joint Geometrical and Statistical Alignment for Visual Domain Adaptation (195 citations)
  • Importance Weighted Adversarial Nets for Partial Domain Adaptation (173 citations)

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

  • Artificial intelligence
  • Computer vision
  • Operating system

Wanqing Li mainly investigates Artificial intelligence, Pattern recognition, Convolutional neural network, RGB color model and Feature extraction. In his study, Wanqing Li carries out multidisciplinary Artificial intelligence and Construct research. His Pattern recognition research incorporates themes from Kernel, Computer vision, Robustness and Joint.

His research investigates the connection with Computer vision and areas like Neocognitron which intersect with concerns in Segmentation. His RGB color model study combines topics from a wide range of disciplines, such as Modality and Deep learning. The various areas that Wanqing Li examines in his Feature extraction study include Sparse approximation and Gesture, Gesture recognition.

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.

Top Publications

The genome of the choanoflagellate Monosiga brevicollis and the origin of metazoans.

Nicole King;M Jody Westbrook;Susan L Young;Alan Kuo.
Nature (2008)

1070 Citations

Action recognition based on a bag of 3D points

Wanqing Li;Zhengyou Zhang;Zicheng Liu.
computer vision and pattern recognition (2010)

963 Citations

Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN

Shuai Li;Wanqing Li;Chris Cook;Ce Zhu.
computer vision and pattern recognition (2018)

260 Citations

Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks

Pichao Wang;Zhaoyang Li;Yonghong Hou;Wanqing Li.
acm multimedia (2016)

250 Citations

A molecular brake in the kinase hinge region regulates the activity of receptor tyrosine kinases.

Huaibin Chen;Jinghong Ma;Wanqing Li;Anna V. Eliseenkova.
Molecular Cell (2007)

245 Citations

Action Recognition From Depth Maps Using Deep Convolutional Neural Networks

Pichao Wang;Wanqing Li;Zhimin Gao;Jing Zhang.
IEEE Transactions on Human-Machine Systems (2016)

217 Citations

Skeleton Optical Spectra-Based Action Recognition Using Convolutional Neural Networks

Yonghong Hou;Zhaoyang Li;Pichao Wang;Wanqing Li.
IEEE Transactions on Circuits and Systems for Video Technology (2018)

211 Citations

Expandable Data-Driven Graphical Modeling of Human Actions Based on Salient Postures

Wanqing Li;Zhengyou Zhang;Zicheng Liu.
IEEE Transactions on Circuits and Systems for Video Technology (2008)

202 Citations

RGB-D-based human motion recognition with deep learning: A survey

Pichao Wang;Wanqing Li;Philip O Ogunbona;Jun Wan.
Computer Vision and Image Understanding (2018)

198 Citations

Joint Geometrical and Statistical Alignment for Visual Domain Adaptation

Jing Zhang;Wanqing Li;Philip Ogunbona.
computer vision and pattern recognition (2017)

195 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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