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 40 Citations 7,204 141 World Ranking 4592 National Ranking 69

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Huazhu Fu mainly focuses on Artificial intelligence, Pattern recognition, Computer vision, Segmentation and Image segmentation. His work on Deep learning, Feature extraction, Salient and Cluster analysis as part of general Artificial intelligence study is frequently connected to Constraint, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. As a part of the same scientific study, Huazhu Fu usually deals with the Pattern recognition, concentrating on RGB color model and frequently concerns with Saliency map, Feature matching and Mutual exclusion.

His Computer vision research is multidisciplinary, relying on both Representation and Identification. The various areas that Huazhu Fu examines in his Segmentation study include Object and Object based. His work focuses on many connections between Image segmentation and other disciplines, such as Glaucoma, that overlap with his field of interest in Fundus and Optical imaging.

His most cited work include:

  • Cluster-Based Co-Saliency Detection (295 citations)
  • Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation (293 citations)
  • CE-Net: Context Encoder Network for 2D Medical Image Segmentation (251 citations)

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

Huazhu Fu mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Segmentation and Deep learning. His Glaucoma research extends to the thematically linked field of Artificial intelligence. His Pattern recognition study combines topics in areas such as RGB color model, Focus, Leverage and Cluster analysis.

His work in the fields of Image overlaps with other areas such as Constraint. His Segmentation study integrates concerns from other disciplines, such as Pixel and Fundus, Optic disc, Optic cup. His Deep learning research incorporates themes from Image processing, Robustness and Color space.

He most often published in these fields:

  • Artificial intelligence (86.86%)
  • Pattern recognition (44.57%)
  • Computer vision (36.57%)

What were the highlights of his more recent work (between 2020-2021)?

  • Artificial intelligence (86.86%)
  • Segmentation (34.29%)
  • Pattern recognition (44.57%)

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

His main research concerns Artificial intelligence, Segmentation, Pattern recognition, Deep learning and Machine learning. His work carried out in the field of Artificial intelligence brings together such families of science as Fundus and Computer vision. His Computer vision study incorporates themes from Salient, Code and Salience.

His Segmentation research integrates issues from Discriminative model and Similarity. He combines subjects such as Image, Feature, Medical diagnosis and Hash function with his study of Pattern recognition. His Image segmentation research includes elements of Retinal and Optical coherence tomography.

Between 2020 and 2021, his most popular works were:

  • ASIF-Net: Attention Steered Interweave Fusion Network for RGB-D Salient Object Detection (31 citations)
  • Salient Object Detection in the Deep Learning Era: An In-depth Survey. (22 citations)
  • Re-thinking Co-Salient Object Detection. (9 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

Huazhu Fu focuses on Artificial intelligence, Machine learning, Field, Deep learning and Feature extraction. The Artificial intelligence study combines topics in areas such as Fundus and Computer vision. His research in Computer vision intersects with topics in Salience and Code.

His work deals with themes such as Salient object detection, Robustness and Taxonomy, which intersect with Machine learning. The study incorporates disciplines such as Depth map, Salient, Convolutional neural network and Object detection in addition to Feature extraction. Huazhu Fu has researched Image segmentation in several fields, including Pixel, Optical coherence tomography and Retinal.

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

CE-Net: Context Encoder Network for 2D Medical Image Segmentation

Zaiwang Gu;Jun Cheng;Huazhu Fu;Kang Zhou.
IEEE Transactions on Medical Imaging (2019)

458 Citations

Cluster-Based Co-Saliency Detection

Huazhu Fu;Xiaochun Cao;Zhuowen Tu.
IEEE Transactions on Image Processing (2013)

366 Citations

Diversity-induced Multi-view Subspace Clustering

Xiaochun Cao;Changqing Zhang;Huazhu Fu;Si Liu.
computer vision and pattern recognition (2015)

320 Citations

Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation

Huazhu Fu;Jun Cheng;Yanwu Xu;Damon Wing Kee Wong.
IEEE Transactions on Medical Imaging (2018)

302 Citations

DeepVessel: Retinal Vessel Segmentation via Deep Learning and Conditional Random Field

Huazhu Fu;Yanwu Xu;Stephen Lin;Damon Wing Kee Wong.
medical image computing and computer assisted intervention (2016)

280 Citations

Retinal vessel segmentation via deep learning network and fully-connected conditional random fields

Huazhu Fu;Yanwu Xu;Damon Wing Kee Wong;Jiang Liu.
international symposium on biomedical imaging (2016)

231 Citations

Low-Rank Tensor Constrained Multiview Subspace Clustering

Changqing Zhang;Huazhu Fu;Si Liu;Guangcan Liu.
international conference on computer vision (2015)

215 Citations

Generalized Latent Multi-View Subspace Clustering

Changqing Zhang;Huazhu Fu;Qinghua Hu;Xiaochun Cao.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2020)

167 Citations

Latent Multi-view Subspace Clustering

Changqing Zhang;Qinghua Hu;Huazhu Fu;Pengfei Zhu.
computer vision and pattern recognition (2017)

163 Citations

Disc-Aware Ensemble Network for Glaucoma Screening From Fundus Image

Huazhu Fu;Jun Cheng;Yanwu Xu;Changqing Zhang.
IEEE Transactions on Medical Imaging (2018)

153 Citations

Best Scientists Citing Huazhu Fu

Huchuan Lu

Huchuan Lu

Dalian University of Technology

Publications: 35

Jianbing Shen

Jianbing Shen

Beijing Institute of Technology

Publications: 35

Junwei Han

Junwei Han

Northwestern Polytechnical University

Publications: 28

Ling Shao

Ling Shao

Inception Institute of Artificial Intelligence

Publications: 28

Zhi Liu

Zhi Liu

Shanghai University

Publications: 27

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 26

Dinggang Shen

Dinggang Shen

ShanghaiTech University

Publications: 26

Ming-Ming Cheng

Ming-Ming Cheng

Nankai University

Publications: 26

Feiping Nie

Feiping Nie

Northwestern Polytechnical University

Publications: 25

Pheng-Ann Heng

Pheng-Ann Heng

Chinese University of Hong Kong

Publications: 24

Xi Peng

Xi Peng

Sichuan University

Publications: 23

Wenguan Wang

Wenguan Wang

ETH Zurich

Publications: 23

Sam Kwong

Sam Kwong

City University of Hong Kong

Publications: 20

Hong Qin

Hong Qin

Stony Brook University

Publications: 19

Yefeng Zheng

Yefeng Zheng

Tencent (China)

Publications: 19

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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