D-Index & Metrics Best Publications

D-Index & Metrics

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 43 Citations 7,514 270 World Ranking 3962 National Ranking 365

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary scientific interests are in Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Machine learning. While working in this field, Hongxun Yao studies both Artificial intelligence and Affect. His Pattern recognition research is multidisciplinary, incorporating perspectives in Recurrent neural network, Image, Visual Word and Background subtraction.

The Feature extraction study combines topics in areas such as Dimension, Solid modeling, Histogram, RGB color model and Kernel. His research integrates issues of Active appearance model, Sparse approximation, Neural coding, Convolutional neural network and Robustness in his study of Eye tracking. His work deals with themes such as Landmark and Mobile device, which intersect with Discriminative model.

His most cited work include:

  • Hedged Deep Tracking (502 citations)
  • Sparse coding based visual tracking: Review and experimental comparison (241 citations)
  • Auto-encoder based dimensionality reduction (194 citations)

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

His main research concerns Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Machine learning. Image, Discriminative model, Feature, Image retrieval and Video tracking are the primary areas of interest in his Artificial intelligence study. His Image retrieval research is multidisciplinary, relying on both Information retrieval and Support vector machine.

His Pattern recognition research integrates issues from Contextual image classification, Histogram, Object and Representation. His Computer vision study often links to related topics such as Robustness. In most of his Feature extraction studies, his work intersects topics such as Visualization.

He most often published in these fields:

  • Artificial intelligence (81.27%)
  • Pattern recognition (43.50%)
  • Computer vision (42.30%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (81.27%)
  • Pattern recognition (43.50%)
  • Feature (9.37%)

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

Artificial intelligence, Pattern recognition, Feature, Object and Image are his primary areas of study. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Computer vision. His Computer vision study combines topics from a wide range of disciplines, such as Computational complexity theory and Frame.

His Pattern recognition research incorporates themes from 3D reconstruction and Recurrent neural network. His Feature study combines topics in areas such as Deep learning and Pattern recognition. His research in Image intersects with topics in Range and Visualization.

Between 2017 and 2021, his most popular works were:

  • Predicting Personalized Image Emotion Perceptions in Social Networks (96 citations)
  • Hedging Deep Features for Visual Tracking (66 citations)
  • Pix2Vox: Context-Aware 3D Reconstruction From Single and Multi-View Images (47 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

Hongxun Yao mainly investigates Artificial intelligence, Pattern recognition, Feature, Computer vision and Convolutional neural network. He incorporates Artificial intelligence and Action recognition in his studies. The study incorporates disciplines such as Recurrent neural network, Quantization and Hash function in addition to Pattern recognition.

In general Computer vision study, his work on Texture and Artifact often relates to the realm of Noise, thereby connecting several areas of interest. His Convolutional neural network research is multidisciplinary, relying on both Image processing, Artificial neural network and Eye tracking. The Feature extraction study combines topics in areas such as Machine learning and Robustness.

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

Hedged Deep Tracking

Yuankai Qi;Shengping Zhang;Lei Qin;Hongxun Yao.
computer vision and pattern recognition (2016)

539 Citations

Sparse coding based visual tracking: Review and experimental comparison

Shengping Zhang;Hongxun Yao;Xin Sun;Xiusheng Lu.
Pattern Recognition (2013)

319 Citations

Auto-encoder based dimensionality reduction

Yasi Wang;Hongxun Yao;Sicheng Zhao.
Neurocomputing (2016)

278 Citations

Deep Feature Fusion for VHR Remote Sensing Scene Classification

Souleyman Chaib;Huan Liu;Yanfeng Gu;Hongxun Yao.
IEEE Transactions on Geoscience and Remote Sensing (2017)

245 Citations

Location Discriminative Vocabulary Coding for Mobile Landmark Search

Rongrong Ji;Ling-Yu Duan;Jie Chen;Hongxun Yao.
International Journal of Computer Vision (2012)

205 Citations

Exploring Principles-of-Art Features For Image Emotion Recognition

Sicheng Zhao;Yue Gao;Xiaolei Jiang;Hongxun Yao.
acm multimedia (2014)

184 Citations

Continuous Probability Distribution Prediction of Image Emotions via Multitask Shared Sparse Regression

Sicheng Zhao;Hongxun Yao;Yue Gao;Rongrong Ji.
IEEE Transactions on Multimedia (2017)

163 Citations

Robust visual tracking based on online learning sparse representation

Shengping Zhang;Hongxun Yao;Huiyu Zhou;Xin Sun.
Neurocomputing (2013)

142 Citations

An image fragile watermark scheme based on chaotic image pattern and pixel-pairs

Shao-Hui Liu;Hong-Xun Yao;Wen Gao;Yong-Liang Liu.
Applied Mathematics and Computation (2007)

136 Citations

Trajectory based event tactics analysis in broadcast sports video

Guangyu Zhu;Qingming Huang;Changsheng Xu;Yong Rui.
acm multimedia (2007)

129 Citations

Best Scientists Citing Hongxun Yao

Rongrong Ji

Rongrong Ji

Xiamen University

Publications: 52

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 33

Sicheng Zhao

Sicheng Zhao

University of California, Berkeley

Publications: 32

Wen Gao

Wen Gao

Peking University

Publications: 30

Tiejun Huang

Tiejun Huang

Peking University

Publications: 29

Qingming Huang

Qingming Huang

Chinese Academy of Sciences

Publications: 28

Ling-Yu Duan

Ling-Yu Duan

Peking University

Publications: 27

Ming-Hsuan Yang

Ming-Hsuan Yang

University of California, Merced

Publications: 27

Ling Shao

Ling Shao

Inception Institute of Artificial Intelligence

Publications: 24

Yue Gao

Yue Gao

Tsinghua University

Publications: 24

Tao Mei

Tao Mei

Jingdong (China)

Publications: 23

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 21

Jiebo Luo

Jiebo Luo

University of Rochester

Publications: 21

Houqiang Li

Houqiang Li

University of Science and Technology of China

Publications: 20

Guiguang Ding

Guiguang Ding

Tsinghua University

Publications: 20

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

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