H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 39 Citations 7,629 224 World Ranking 2594 National Ranking 262

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

His primary areas of investigation include Artificial intelligence, Computer vision, Artificial neural network, Pattern recognition and Convolutional neural network. As part of his studies on Artificial intelligence, Yue Huang often connects relevant subjects like Algorithm. His research on Computer vision frequently links to adjacent areas such as Probabilistic logic.

The Pattern recognition study combines topics in areas such as Bayesian network, Iterative reconstruction, Compressed sensing and Bayesian inference. Yue Huang has researched Convolutional neural network in several fields, including Feature extraction, Image segmentation, Kernel and Robustness. His Deep learning study combines topics in areas such as Discriminative model, Feature learning and Categorization.

His most cited work include:

  • Removing Rain from Single Images via a Deep Detail Network (355 citations)
  • A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation (224 citations)
  • A fusion-based enhancing method for weakly illuminated images (168 citations)

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

Yue Huang mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Deep learning and Image. Segmentation, Artificial neural network, Compressed sensing, Convolutional neural network and Feature are the subjects of his Artificial intelligence studies. His study in Convolutional neural network is interdisciplinary in nature, drawing from both Pyramid, Training set, Data mining and Pyramid.

The concepts of his Pattern recognition study are interwoven with issues in Supervised learning and Noise reduction. His biological study spans a wide range of topics, including Transfer of learning, Labeled data and Robustness. In the field of Image, his study on Single image overlaps with subjects such as Naturalness and Underwater.

He most often published in these fields:

  • Artificial intelligence (84.25%)
  • Pattern recognition (47.24%)
  • Computer vision (30.71%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (84.25%)
  • Pattern recognition (47.24%)
  • Deep learning (22.05%)

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

Yue Huang focuses on Artificial intelligence, Pattern recognition, Deep learning, Discriminative model and Convolutional neural network. As part of his studies on Artificial intelligence, Yue Huang often connects relevant areas like Machine learning. His Pattern recognition research is multidisciplinary, incorporating perspectives in Normalization, Feature, Interpolation, Supervised learning and Generative grammar.

Yue Huang interconnects Robustness and Computer vision in the investigation of issues within Deep learning. Yue Huang combines subjects such as Classifier, Feature and Feature vector with his study of Discriminative model. His Convolutional neural network research includes themes of Algorithm, Error detection and correction, Compressed sensing and Labeled data.

Between 2019 and 2021, his most popular works were:

  • Lightweight Pyramid Networks for Image Deraining (59 citations)
  • Harmonizing Transferability and Discriminability for Adapting Object Detectors (20 citations)
  • Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches. (17 citations)

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

  • Artificial intelligence
  • Machine learning
  • Algorithm

Artificial intelligence, Pattern recognition, Feature extraction, Segmentation and Artificial neural network are his primary areas of study. Yue Huang does research in Artificial intelligence, focusing on Deep learning specifically. His work deals with themes such as Annotation, Entropy and Precision medicine, which intersect with Deep learning.

His Pattern recognition study combines topics from a wide range of disciplines, such as Adversarial system, Image synthesis, Image, Translation and Supervised learning. His work on Image segmentation as part of general Segmentation study is frequently connected to Weighted network, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His biological study deals with issues like Pyramid, which deal with fields such as Convolutional neural network.

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

A review of the use of recycled solid waste materials in asphalt pavements

Yue Huang;Roger N. Bird;Oliver Heidrich.
Resources Conservation and Recycling (2007)

653 Citations

Removing Rain from Single Images via a Deep Detail Network

Xueyang Fu;Jiabin Huang;Delu Zeng;Yue Huang.
computer vision and pattern recognition (2017)

414 Citations

A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation

Xueyang Fu;Delu Zeng;Yue Huang;Xiao-Ping Zhang.
computer vision and pattern recognition (2016)

408 Citations

Development of a life cycle assessment tool for construction and maintenance of asphalt pavements

Yue Huang;Roger Bird;Oliver Heidrich.
Journal of Cleaner Production (2009)

353 Citations

HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks

Chuan Shi;Xiangnan Kong;Yue Huang;Philip S. Yu.
IEEE Transactions on Knowledge and Data Engineering (2014)

244 Citations

A retinex-based enhancing approach for single underwater image

Xueyang Fu;Peixian Zhuang;Yue Huang;Yinghao Liao.
international conference on image processing (2014)

210 Citations

A fusion-based enhancing method for weakly illuminated images

Xueyang Fu;Delu Zeng;Yue Huang;Yinghao Liao.
Signal Processing (2016)

207 Citations

A comparative study of the emissions by road maintenance works and the disrupted traffic using life cycle assessment and micro-simulation

Yue Huang;Roger Bird;Margaret Bell.
Transportation Research Part D-transport and Environment (2009)

182 Citations

A Probabilistic Method for Image Enhancement With Simultaneous Illumination and Reflectance Estimation

Xueyang Fu;Yinghao Liao;Delu Zeng;Yue Huang.
IEEE Transactions on Image Processing (2015)

180 Citations

p25α Relocalizes in Oligodendroglia from Myelin to Cytoplasmic Inclusions in Multiple System Atrophy

Yun Ju C. Song;Ditte M.S. Lundvig;Yue Huang;Wei Ping Gai.
American Journal of Pathology (2007)

165 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Yue Huang

Glenda M. Halliday

Glenda M. Halliday

University of Sydney

Publications: 66

Gregor K. Wenning

Gregor K. Wenning

Innsbruck Medical University

Publications: 29

Jiaying Liu

Jiaying Liu

Peking University

Publications: 29

Chuan Shi

Chuan Shi

Beijing University of Posts and Telecommunications

Publications: 28

Deyu Meng

Deyu Meng

Xi'an Jiaotong University

Publications: 24

Poul Henning Jensen

Poul Henning Jensen

Aarhus University

Publications: 20

Vishal M. Patel

Vishal M. Patel

Johns Hopkins University

Publications: 20

Gabor G. Kovacs

Gabor G. Kovacs

University of Toronto

Publications: 20

Shaopeng Wu

Shaopeng Wu

Wuhan University of Technology

Publications: 19

Tiago F. Outeiro

Tiago F. Outeiro

University of Göttingen

Publications: 19

Philip S. Yu

Philip S. Yu

University of Illinois at Chicago

Publications: 19

Yu-Fei Wu

Yu-Fei Wu

Shenzhen University

Publications: 18

Kurt A. Jellinger

Kurt A. Jellinger

Medical University of Vienna

Publications: 17

Ming-Hsuan Yang

Ming-Hsuan Yang

University of California, Merced

Publications: 16

Wassilios G. Meissner

Wassilios G. Meissner

University of Otago

Publications: 15

John B.J. Kwok

John B.J. Kwok

University of Sydney

Publications: 14

Something went wrong. Please try again later.