Dongdong Chen

16.5k citations
178 papers · 9.1k indexed · 11 hit papers · h-index 46

Dongdong Chen

169 papers receiving 8.9k citations

Hit Papers

Equivariant Multi-Modal...652019202620212023250500750

Peers

Dongdong Chen
Comparison fields: 5 of 202
  • Computer Vision and Pattern Recognition 5.6k
  • Computer Graphics and Computer-Aided Design 522
  • Media Technology 1.0k
  • Artificial Intelligence 1.6k
  • Signal Processing 375
Replace Tsung-Yi Lin with:
Tsung-Yi Lin United States
Ping Li China
Liang Lin China
Dong Liu China
Peter Johansen Denmark
Huiyu Zhou United Kingdom
Jianfei Cai Singapore
Zeming Lin China
Gao Huang China
Xiaoou Tang Hong Kong
Dongdong Chen relative to Tsung-Yi Lin United States Tsung-Yi Lin's profile →
Citations per field
00.5×1.6×
Tsung-Yi Lin · 1×
Citations per year

Countries citing papers authored by Dongdong Chen

Since Specialization
Citations

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

Fields of papers citing papers by Dongdong Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20247
3 20241
4 20240
5 20241
6 20249
7 202410
8 20233
9 20232
10 202340
11 20234
12 202110
13 202146
14 202038
15
Passport-aware Normalization for Deep Model Protection
20203
16 201940
17
Deep Fully Convolutional Network for MR Fingerprinting
20191
18 201967
19
A deep learning approach for Magnetic Resonance Fingerprinting.
20181
20 20144

About Dongdong Chen

Dongdong Chen is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 178 papers that have together received 9.1k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (24 papers), Advanced Neural Network Applications (20 papers), Adversarial Robustness in Machine Learning (17 papers), Advanced Image Processing Techniques (15 papers), Image Enhancement Techniques (13 papers), Domain Adaptation and Few-Shot Learning (12 papers), Multimodal Machine Learning Applications (12 papers) and Digital Media Forensic Detection (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.6k citations), Computer Graphics and Computer-Aided Design (522 citations) and Media Technology (1.0k citations). Dongdong Chen has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Lu Yuan, Nenghai Yu, Jing Liao, Weiming Zhang, Xiyang Dai, Yinpeng Chen, Mengchen Liu, Zicheng Liu, Xiaoyi Dong and Jianmin Bao. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Image Processing, ACM Transactions on Graphics and Sensors and Actuators B Chemical.

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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