Tianyu Ding

480 citations
18 papers · 191 · h-index 5

Impact in

Papers in

Tianyu Ding

15 papers receiving 190 citations

Peers

Tianyu Ding
Comparison fields: 5 of 46
  • Computer Vision and Pattern Recognition 137
  • Computer Graphics and Computer-Aided Design 14
  • Media Technology 35
  • Signal Processing 20
  • Instrumentation 3
Replace Frederic Besse with:
Frederic Besse United States
Tal Remez Israel
Min Jin Chong United States
Zhiguang Yang China
Abhijith Punnappurath South Korea
Haibo Chen China
Gangyi Jiang China
Liying Lu Hong Kong
Huaijia Lin Hong Kong
Thibault Napoléon France
Tianyu Ding relative to Frederic Besse United States Frederic Besse's profile →
Citations per field
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Frederic Besse · 1×
Citations per year

Countries citing papers authored by Tianyu Ding

Since Specialization
Citations

This map shows the geographic impact of Tianyu Ding'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 Tianyu Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tianyu Ding more than expected).

Fields of papers citing papers by Tianyu Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tianyu Ding. 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 Tianyu Ding. The network helps show where Tianyu Ding may publish in the future.

Co-authors

The 25 scholars most cited alongside Tianyu Ding, 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 Tianyu Ding Line = papers co-authored together Tianyu Ding links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 202275
2 202164
3 202524
4 20226
5 20244
6 20233
7
Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms
20213
8 20243
9 20252
10
Sentiment Analysis and Political Party Classification in 2016 U.S. President Debates in Twitter
20172
11 20241
12 20231
13 20251
14
Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach
20211
15 20251
16 20240
17 20250
18 20250

About Tianyu Ding

Tianyu Ding is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Statistical and Nonlinear Physics and Computational Mechanics, having authored 18 papers that have together received 191 indexed citations. Recurring topics across this work include Image Processing Techniques and Applications (3 papers), Advanced Vision and Imaging (3 papers), Advanced Image Processing Techniques (2 papers), Smart Agriculture and AI (2 papers), Image Enhancement Techniques (1 paper), Surface Roughness and Optical Measurements (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Face and Expression Recognition (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (137 citations), Computer Graphics and Computer-Aided Design (14 citations), Media Technology (35 citations), Signal Processing (20 citations) and Instrumentation (3 citations). Tianyu Ding has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Luming Liang, Zhicheng Geng, Zhihui Zhu, Yang Gao, Jing Huo, Wenbin Li, Yuxin Li, Jiebo Luo, Jiwen Wang and Tong Shen. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Circuits and Systems for Video Technology, Soil and Tillage Research, Knowledge and Information Systems and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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