H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 36 Citations 5,583 226 World Ranking 5612 National Ranking 547

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Statistics

His scientific interests lie mostly in Artificial intelligence, Computer vision, Image quality, Visualization and Distortion. His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning and Pattern recognition. His work deals with themes such as Artificial neural network and Spoofing attack, which intersect with Pattern recognition.

In Computer vision, Shiqi Wang works on issues like Ringing, which are connected to Visual artifact. The various areas that Shiqi Wang examines in his Image quality study include Image resolution, Data mining, Histogram, Entropy and Image gradient. His Visualization research incorporates elements of Brightness, Tone mapping and Digital image processing.

His most cited work include:

  • Domain Generalization with Adversarial Feature Learning (244 citations)
  • SSIM-Motivated Rate-Distortion Optimization for Video Coding (157 citations)
  • Saliency-Guided Quality Assessment of Screen Content Images (155 citations)

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

His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Coding. Shiqi Wang frequently studies issues relating to Machine learning and Artificial intelligence. His work on Data compression, Motion compensation and Human visual system model as part of general Computer vision research is often related to Distortion, thus linking different fields of science.

His studies in Pattern recognition integrate themes in fields like Image, Spoofing attack and Feature. His work on Coding tree unit and Quadtree as part of general Algorithm study is frequently linked to Rate control and Random access, bridging the gap between disciplines. His research in Coding intersects with topics in Low complexity, Quantization, Computational complexity theory, Encoder and Reference frame.

He most often published in these fields:

  • Artificial intelligence (70.18%)
  • Computer vision (31.58%)
  • Pattern recognition (25.61%)

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

  • Artificial intelligence (70.18%)
  • Pattern recognition (25.61%)
  • Coding (22.11%)

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

His primary areas of investigation include Artificial intelligence, Pattern recognition, Coding, Algorithm and Machine learning. His research on Artificial intelligence often connects related topics like Computer vision. His Pattern recognition research integrates issues from Regularization, Representation, Face and Spoofing attack.

Shiqi Wang interconnects Data mining, Codec, Encoder, Video quality and Robustness in the investigation of issues within Coding. His work in the fields of Decoding methods overlaps with other areas such as Random access, Rate control and Block. His work on Convolutional neural network and Artificial neural network as part of general Machine learning research is frequently linked to Set, bridging the gap between disciplines.

Between 2019 and 2021, his most popular works were:

  • Image and Video Compression With Neural Networks: A Review (57 citations)
  • Single Image Deraining: From Model-Based to Data-Driven and Beyond. (32 citations)
  • Image Quality Assessment: Unifying Structure and Texture Similarity. (27 citations)

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

  • Artificial intelligence
  • Computer vision
  • Statistics

Shiqi Wang focuses on Artificial intelligence, Pattern recognition, Machine learning, Coding and Algorithm. His study in Convolutional neural network, Deep learning, Feature, Feature extraction and Visualization falls under the purview of Artificial intelligence. To a larger extent, Shiqi Wang studies Computer vision with the aim of understanding Feature extraction.

Image processing is closely connected to Salience in his research, which is encompassed under the umbrella topic of Computer vision. His Pattern recognition research includes elements of Pixel, Regularization, Representation and Image restoration. His study in Coding is interdisciplinary in nature, drawing from both Encoder and Decoding methods.

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

Domain Generalization with Adversarial Feature Learning

Haoliang Li;Sinno Jialin Pan;Shiqi Wang;Alex C. Kot.
computer vision and pattern recognition (2018)

244 Citations

Saliency-Guided Quality Assessment of Screen Content Images

Ke Gu;Shiqi Wang;Huan Yang;Weisi Lin.
IEEE Transactions on Multimedia (2016)

179 Citations

SSIM-Motivated Rate-Distortion Optimization for Video Coding

Shiqi Wang;A. Rehman;Zhou Wang;Siwei Ma.
IEEE Transactions on Circuits and Systems for Video Technology (2012)

175 Citations

A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images

Shiqi Wang;Kede Ma;Hojatollah Yeganeh;Zhou Wang.
IEEE Signal Processing Letters (2015)

154 Citations

Group-Sensitive Triplet Embedding for Vehicle Reidentification

Yan Bai;Yihang Lou;Feng Gao;Shiqi Wang.
IEEE Transactions on Multimedia (2018)

135 Citations

Analysis of Distortion Distribution for Pooling in Image Quality Prediction

Ke Gu;Shiqi Wang;Guangtao Zhai;Weisi Lin.
IEEE Transactions on Broadcasting (2016)

123 Citations

Quality Prediction of Asymmetrically Distorted Stereoscopic 3D Images

Jiheng Wang;Abdul Rehman;Kai Zeng;Shiqi Wang.
IEEE Transactions on Image Processing (2015)

121 Citations

Perceptual Video Coding Based on SSIM-Inspired Divisive Normalization

Shiqi Wang;A. Rehman;Zhou Wang;Siwei Ma.
IEEE Transactions on Image Processing (2013)

117 Citations

Blind Quality Assessment of Tone-Mapped Images Via Analysis of Information, Naturalness, and Structure

Ke Gu;Shiqi Wang;Guangtao Zhai;Siwei Ma.
IEEE Transactions on Multimedia (2016)

112 Citations

Utility-Driven Adaptive Preprocessing for Screen Content Video Compression

Shiqi Wang;Xinfeng Zhang;Xianming Liu;Jian Zhang.
IEEE Transactions on Multimedia (2017)

94 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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Top Scientists Citing Shiqi Wang

Ke Gu

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