H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 32 Citations 4,408 161 World Ranking 7487 National Ranking 717

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Algorithm

Hongliang Li mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Image segmentation. In his study, Generalization is inextricably linked to Machine learning, which falls within the broad field of Artificial intelligence. His Pattern recognition research is multidisciplinary, relying on both Edge detection and Discrete cosine transform.

His study looks at the relationship between Computer vision and topics such as Robustness, which overlap with Automatic summarization, Semantic analysis, Face detection and Cut. His Feature extraction study which covers Image texture that intersects with Histogram and Scale space. As a part of the same scientific family, Hongliang Li mostly works in the field of Image segmentation, focusing on Similarity and, on occasion, Word error rate and SimRank.

His most cited work include:

  • A Co-Saliency Model of Image Pairs (276 citations)
  • Waterloo Exploration Database: New Challenges for Image Quality Assessment Models (246 citations)
  • A Fast HEVC Inter CU Selection Method Based on Pyramid Motion Divergence (181 citations)

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

Hongliang Li focuses on Artificial intelligence, Pattern recognition, Computer vision, Segmentation and Image segmentation. Feature extraction, Object detection, Image, Feature and Pascal are among the areas of Artificial intelligence where the researcher is concentrating his efforts. Hongliang Li works mostly in the field of Feature, limiting it down to topics relating to Image quality and, in certain cases, Distortion, Machine learning and Metric, as a part of the same area of interest.

His studies in Pattern recognition integrate themes in fields like Contextual image classification, Pixel, Histogram and Cluster analysis. Computer vision is frequently linked to Visualization in his study. His Segmentation research integrates issues from Object, Minimum bounding box, Embedding and Saliency map.

He most often published in these fields:

  • Artificial intelligence (79.69%)
  • Pattern recognition (53.12%)
  • Computer vision (39.06%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (79.69%)
  • Pattern recognition (53.12%)
  • Segmentation (29.69%)

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

The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Segmentation, Pascal and Computer vision. His study in Artificial intelligence focuses on Feature extraction, Feature, Image, Image segmentation and Object detection. His research investigates the connection between Pattern recognition and topics such as Object that intersect with problems in Sentence.

His study in Segmentation is interdisciplinary in nature, drawing from both Parsing, Classifier, Pixel, Embedding and Minimum bounding box. His work in Pascal tackles topics such as Convolutional neural network which are related to areas like Data mining and Disjoint sets. His study on Single image is often connected to Haze as part of broader study in Computer vision.

Between 2018 and 2021, his most popular works were:

  • VisDrone-DET2019: The Vision Meets Drone Object Detection in Image Challenge Results (28 citations)
  • Group Maximum Differentiation Competition: Model Comparison with Few Samples (20 citations)
  • Simultaneously Detecting and Counting Dense Vehicles From Drone Images (19 citations)

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

  • Artificial intelligence
  • Computer vision
  • Algorithm

His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Pascal, Segmentation and Object detection. His Artificial intelligence study incorporates themes from Algorithm and Computer vision. He works in the field of Pattern recognition, namely Discriminative model.

The concepts of his Pascal study are interwoven with issues in Feature fusion, Image segmentation, Embedding, Cluster analysis and Binary classification. His biological study spans a wide range of topics, including Minimum bounding box and Convolutional neural network. The various areas that he examines in his Object detection study include Remote sensing and Detector.

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 Co-Saliency Model of Image Pairs

Hongliang Li;King Ngi Ngan.
IEEE Transactions on Image Processing (2011)

276 Citations

Waterloo Exploration Database: New Challenges for Image Quality Assessment Models

Kede Ma;Zhengfang Duanmu;Qingbo Wu;Zhou Wang.
IEEE Transactions on Image Processing (2017)

252 Citations

A Fast HEVC Inter CU Selection Method Based on Pyramid Motion Divergence

Jian Xiong;Hongliang Li;Qingbo Wu;Fanman Meng.
IEEE Transactions on Multimedia (2014)

230 Citations

Multimodal medical image fusion based on IHS and PCA

Changtao He;Quanxi Liu;Hongliang Li;Haixu Wang.
Procedia Engineering (2010)

209 Citations

Object Co-Segmentation Based on Shortest Path Algorithm and Saliency Model

Fanman Meng;Hongliang Li;Guanghui Liu;King Ngi Ngan.
IEEE Transactions on Multimedia (2012)

162 Citations

Blind Image Quality Assessment Based on Multichannel Feature Fusion and Label Transfer

Qingbo Wu;Hongliang Li;Fanman Meng;King N. Ngan.
IEEE Transactions on Circuits and Systems for Video Technology (2016)

130 Citations

Co-Salient Object Detection From Multiple Images

Hongliang Li;Fanman Meng;King Ngi Ngan.
IEEE Transactions on Multimedia (2013)

112 Citations

A Multiple Visual Models Based Perceptive Analysis Framework for Multilevel Video Summarization

Junyong You;Guizhong Liu;Li Sun;Hongliang Li.
IEEE Transactions on Circuits and Systems for Video Technology (2007)

111 Citations

Saliency model-based face segmentation and tracking in head-and-shoulder video sequences

Hongliang Li;King N. Ngan.
Journal of Visual Communication and Image Representation (2008)

101 Citations

LETRIST: Locally Encoded Transform Feature Histogram for Rotation-Invariant Texture Classification

Tiecheng Song;Hongliang Li;Fanman Meng;Qingbo Wu.
IEEE Transactions on Circuits and Systems for Video Technology (2018)

93 Citations

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

Contact us

Best Scientists Citing Hongliang Li

Shiqi Wang

Shiqi Wang

City University of Hong Kong

Publications: 32

Zhi Liu

Zhi Liu

Shanghai University

Publications: 29

Zhou Wang

Zhou Wang

University of Waterloo

Publications: 26

Sam Kwong

Sam Kwong

City University of Hong Kong

Publications: 24

Huazhu Fu

Huazhu Fu

Agency for Science, Technology and Research

Publications: 23

Ke Gu

Ke Gu

Beijing University of Technology

Publications: 22

Wangmeng Zuo

Wangmeng Zuo

Harbin Institute of Technology

Publications: 20

Guangtao Zhai

Guangtao Zhai

Shanghai Jiao Tong University

Publications: 20

Weisi Lin

Weisi Lin

Nanyang Technological University

Publications: 20

Lei Zhang

Lei Zhang

Hong Kong Polytechnic University

Publications: 20

Yuming Fang

Yuming Fang

Jiangxi University of Finance and Economics

Publications: 20

Junwei Han

Junwei Han

Northwestern Polytechnical University

Publications: 18

Xiaokang Yang

Xiaokang Yang

Shanghai Jiao Tong University

Publications: 14

Guangming Shi

Guangming Shi

Xidian University

Publications: 14

Junsong Yuan

Junsong Yuan

University at Buffalo, State University of New York

Publications: 13

Wen Gao

Wen Gao

Peking University

Publications: 13

Something went wrong. Please try again later.