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 32 Citations 4,808 168 World Ranking 7490 National Ranking 693

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Yuming Fang mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Image quality. His studies in Visualization, Feature, Histogram, Seam carving and Human visual system model are all subfields of Artificial intelligence research. His biological study spans a wide range of topics, including Salient and Salience.

His Pattern recognition study integrates concerns from other disciplines, such as Image processing, Feature detection and Entropy. The Feature extraction study combines topics in areas such as Luminance, Support vector machine and Image texture. As a member of one scientific family, Yuming Fang mostly works in the field of Image quality, focusing on Local binary patterns and, on occasion, Normalization.

His most cited work include:

  • Saliency Detection in the Compressed Domain for Adaptive Image Retargeting (260 citations)
  • A Saliency Detection Model Using Low-Level Features Based on Wavelet Transform (190 citations)
  • No-Reference Quality Assessment of Contrast-Distorted Images Based on Natural Scene Statistics (184 citations)

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

Yuming Fang focuses on Artificial intelligence, Computer vision, Pattern recognition, Image quality and Feature extraction. His work in the fields of Artificial intelligence, such as Image, Visualization, Feature and Human visual system model, overlaps with other areas such as Distortion. The various areas that Yuming Fang examines in his Computer vision study include Visual attention and Salience.

His Pattern recognition research includes themes of Histogram and Saliency map. His research in Image quality intersects with topics in Transform coding, Machine learning, Data mining and Image fusion. His work deals with themes such as Feature detection, Object detection, Kadir–Brady saliency detector and Image texture, which intersect with Feature extraction.

He most often published in these fields:

  • Artificial intelligence (88.44%)
  • Computer vision (60.69%)
  • Pattern recognition (42.20%)

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

  • Artificial intelligence (88.44%)
  • Computer vision (60.69%)
  • Pattern recognition (42.20%)

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

Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Image are his primary areas of study. Yuming Fang carries out multidisciplinary research, doing studies in Artificial intelligence and Distortion. His research in Computer vision is mostly concerned with View synthesis.

The concepts of his Pattern recognition study are interwoven with issues in Pixel and Feature. His Feature extraction study combines topics in areas such as Object detection, Anomaly detection and Human visual system model. His Image research incorporates elements of Algorithm, Compressed sensing, Chaotic and Light field.

Between 2019 and 2021, his most popular works were:

  • Single Image Deraining: From Model-Based to Data-Driven and Beyond. (32 citations)
  • Deep Guided Learning for Fast Multi-Exposure Image Fusion (18 citations)
  • From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement (17 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

Yuming Fang mainly focuses on Artificial intelligence, Feature extraction, Computer vision, Pattern recognition and Visualization. Yuming Fang incorporates Artificial intelligence and Distortion in his studies. Yuming Fang combines subjects such as RGB color model, Object detection and Benchmark with his study of Feature extraction.

His study in Computer vision is interdisciplinary in nature, drawing from both Scrambling and Compressed sensing. His Pattern recognition research is multidisciplinary, incorporating elements of Contrast, Noise, Image restoration and Norm. His Visualization study combines topics from a wide range of disciplines, such as Recurrent neural network, Feature, Pyramid and Salience.

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

Saliency Detection in the Compressed Domain for Adaptive Image Retargeting

Yuming Fang;Zhenzhong Chen;Weisi Lin;Chia-Wen Lin.
IEEE Transactions on Image Processing (2012)

310 Citations

No-Reference Quality Assessment of Contrast-Distorted Images Based on Natural Scene Statistics

Yuming Fang;Kede Ma;Zhou Wang;Weisi Lin.
IEEE Signal Processing Letters (2015)

242 Citations

A Saliency Detection Model Using Low-Level Features Based on Wavelet Transform

N. Imamoglu;Weisi Lin;Yuming Fang.
IEEE Transactions on Multimedia (2013)

231 Citations

A Video Saliency Detection Model in Compressed Domain

Yuming Fang;Weisi Lin;Zhenzhong Chen;Chia-Ming Tsai.
IEEE Transactions on Circuits and Systems for Video Technology (2014)

212 Citations

Video Saliency Incorporating Spatiotemporal Cues and Uncertainty Weighting

Yuming Fang;Zhou Wang;Weisi Lin;Zhijun Fang.
IEEE Transactions on Image Processing (2014)

187 Citations

Bottom-Up Saliency Detection Model Based on Human Visual Sensitivity and Amplitude Spectrum

Yuming Fang;Weisi Lin;Bu-Sung Lee;Chiew-Tong Lau.
IEEE Transactions on Multimedia (2012)

163 Citations

Perceptual Quality Assessment of Screen Content Images

Huan Yang;Yuming Fang;Weisi Lin.
IEEE Transactions on Image Processing (2015)

160 Citations

Saliency Detection for Stereoscopic Images

Yuming Fang;Junle Wang;Manish Narwaria;Patrick Le Callet.
IEEE Transactions on Image Processing (2014)

154 Citations

No-Reference Quality Assessment for Multiply-Distorted Images in Gradient Domain

Qiaohong Li;Weisi Lin;Yuming Fang.
IEEE Signal Processing Letters (2016)

147 Citations

Saliency-Based Defect Detection in Industrial Images by Using Phase Spectrum

Xiaolong Bai;Yuming Fang;Weisi Lin;Lipo Wang.
IEEE Transactions on Industrial Informatics (2014)

121 Citations

Best Scientists Citing Yuming Fang

Weisi Lin

Weisi Lin

Nanyang Technological University

Publications: 73

Ke Gu

Ke Gu

Beijing University of Technology

Publications: 66

Guangtao Zhai

Guangtao Zhai

Shanghai Jiao Tong University

Publications: 45

Shiqi Wang

Shiqi Wang

City University of Hong Kong

Publications: 38

Sam Kwong

Sam Kwong

City University of Hong Kong

Publications: 31

Guangming Shi

Guangming Shi

Xidian University

Publications: 28

Zhi Liu

Zhi Liu

Shanghai University

Publications: 27

Xiaokang Yang

Xiaokang Yang

Shanghai Jiao Tong University

Publications: 24

Alan C. Bovik

Alan C. Bovik

The University of Texas at Austin

Publications: 22

Jianbing Shen

Jianbing Shen

Beijing Institute of Technology

Publications: 20

Yao Zhao

Yao Zhao

Beijing Jiaotong University

Publications: 19

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 18

Zhou Wang

Zhou Wang

University of Waterloo

Publications: 18

King Ngi Ngan

King Ngi Ngan

University of Electronic Science and Technology of China

Publications: 17

Zhenzhong Chen

Zhenzhong Chen

Wuhan University

Publications: 16

Jiaying Liu

Jiaying Liu

Peking University

Publications: 16

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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