Leiting Chen

1.0k citations
107 papers · 753 · h-index 15

Impact in

Papers in

Leiting Chen

98 papers receiving 719 citations

Peers

Leiting Chen
Comparison fields: 5 of 106
  • Computer Vision and Pattern Recognition 354
  • Computational Mathematics 5
  • Artificial Intelligence 253
  • Media Technology 62
  • Radiology, Nuclear Medicine and Imaging 130
Replace David Tolliver with:
David Tolliver United States
Rudrasis Chakraborty United States
Nicolas Thome France
Jingyong Su China
Farhad Kamangar United States
T. A. Joyce United Kingdom
Chih–Chung Hsu Taiwan
Mohammad Rostami United States
Wenrui Dai China
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Citations per field
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Citations per year

Countries citing papers authored by Leiting Chen

Since Specialization
Citations

This map shows the geographic impact of Leiting Chen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Leiting Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leiting Chen more than expected).

Fields of papers citing papers by Leiting Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leiting Chen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Leiting Chen. The network helps show where Leiting Chen may publish in the future.

Co-authors

The 25 scholars most cited alongside Leiting Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Leiting Chen Line = papers co-authored together Leiting Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 107 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202160
2
A Survey of Video Enhancement Techniques
201258
3 201741
4 201735
5 201829
6 201821
7
Saliency transfer: an example-based method for salient object detection
201620
8 202019
9 201819
10 201619
11 201118
12 201517
13 201615
14 201615
15 200515
16 201212
17 201511
18 202211
19 201511
20 201611

About Leiting Chen

Leiting Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Control and Systems Engineering and Computer Graphics and Computer-Aided Design, having authored 107 papers that have together received 753 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (16 papers), Simulation and Modeling Applications (12 papers), Computer Graphics and Visualization Techniques (12 papers), Human Motion and Animation (8 papers), Multimodal Machine Learning Applications (8 papers), Medical Image Segmentation Techniques (7 papers), Advanced Neural Network Applications (7 papers) and Advanced Image and Video Retrieval Techniques (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (354 citations), Computational Mathematics (5 citations), Artificial Intelligence (253 citations), Media Technology (62 citations) and Radiology, Nuclear Medicine and Imaging (130 citations). Leiting Chen has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Chuan Zhou, Yang Wen, Yu Deng, Yuxiao Guo, Hong Cheng, Xin Li, Jin Ning, Tao Wu, Fan Yang and Jianping Li. Their work appears in journals such as International Journal of Advancements in Computing Technology, Knowledge-Based Systems, Physica A Statistical Mechanics and its Applications, Journal of Visual Communication and Image Representation and Multimedia Tools and Applications.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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