Deng Cai

24.6k citations
231 papers · 15.7k indexed · 10 hit papers · h-index 61

Deng Cai

224 papers receiving 15.2k citations

Hit Papers

CLRNet: Cross ...16020052026201220194008001.2k

Peers

Deng Cai
Comparison fields: 5 of 179
  • Computer Vision and Pattern Recognition 9.8k
  • Computational Mathematics 241
  • Artificial Intelligence 7.0k
  • Media Technology 1.9k
  • Signal Processing 1.4k
Replace Xiaofei He with:
Xiaofei He China
Yun Fu United States
Yong Yu China
Jinhui Tang China
Heng Huang United States
Xinwang Liu China
Xiaochun Cao China
Rongrong Ji China
Xuelong Li China
Xinbo Gao China
Deng Cai relative to Xiaofei He China Xiaofei He's profile →
Citations per field
00.5×1.5×
Xiaofei He · 1×
Citations per year

Countries citing papers authored by Deng Cai

Since Specialization
Citations

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

Fields of papers citing papers by Deng Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20252
3 20243
4 20241
5 20242
6 202313
7 20239
8 202311
9 20237
10 20222
11 202217
12 202036
13 202048
14 201619
15
Non-negative matrix factorization with sinkhorn distance
201620
16
Multi-Manifold Concept Factorization for Data Clustering
20134
17 201337
18
Sparse projections over graph
200815
19
Laplacian Score for Feature Selectionbreakdown →
20051321
20
Tensor Subspace Analysis
2005276

About Deng Cai

Deng Cai is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Media Technology and Computational Mathematics, having authored 231 papers that have together received 15.7k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (76 papers), Image Retrieval and Classification Techniques (57 papers), Face and Expression Recognition (55 papers), Topic Modeling (26 papers), Multimodal Machine Learning Applications (22 papers), Advanced Neural Network Applications (20 papers), Sparse and Compressive Sensing Techniques (18 papers) and Domain Adaptation and Few-Shot Learning (18 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (9.8k citations), Computational Mathematics (241 citations), Artificial Intelligence (7.0k citations), Media Technology (1.9k citations) and Signal Processing (1.4k citations). Deng Cai has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiaofei He, Jiawei Han, Partha Niyogi, Jiawei Han, Wei‐Ying Ma, Chiyuan Zhang, Xuelong Li, Jiajun Bu, Ji-Rong Wen and Chun Chen. Their work appears in journals such as Neurocomputing, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Image Processing, IEEE Transactions on Cybernetics 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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