Da Cao

1.6k citations
45 papers · 1.2k · h-index 17

Impact in

Papers in

Da Cao

43 papers receiving 1.1k citations

Peers

Da Cao
Comparison fields: 5 of 84
  • Computer Vision and Pattern Recognition 537
  • Information Systems 503
  • Computer Science Applications 100
  • Artificial Intelligence 542
  • Computational Mathematics 5
Replace Xiaoxuan Shen with:
Xiaoxuan Shen China
Hai Liu China
Laurent Charlin Canada
Minsuk Kahng United States
Pipei Huang China
Haifeng Liu China
Kan Li China
Xin Xin China
Heung-Nam Kim South Korea
Da Cao relative to Xiaoxuan Shen China Xiaoxuan Shen's profile →
Citations per field
00.5×
Xiaoxuan Shen · 1×
Citations per year

Countries citing papers authored by Da Cao

Since Specialization
Citations

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

Fields of papers citing papers by Da Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018201
2 2020108
3 2017104
4 201994
5 201785
6 202165
7 201952
8 201849
9 201945
10 201634
11 201928
12 202028
13 202025
14 202223
15 201922
16 202020
17 201816
18 202215
19 201915
20 201913

About Da Cao

Da Cao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Computer Science Applications and Computer Networks and Communications, having authored 45 papers that have together received 1.2k indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (22 papers), Video Analysis and Summarization (13 papers), Advanced Image and Video Retrieval Techniques (13 papers), Recommender Systems and Techniques (9 papers), Topic Modeling (7 papers), Online Learning and Analytics (6 papers), Domain Adaptation and Few-Shot Learning (5 papers) and Advanced Graph Neural Networks (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (537 citations), Information Systems (503 citations), Computer Science Applications (100 citations), Artificial Intelligence (542 citations) and Computational Mathematics (5 citations). Da Cao has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Xiangnan He, Liqiang Nie, Xiaochi Wei, Chao Yang, Richang Hong, Tat‐Seng Chua, Yahui An, Zeng YaWen, Qi Tian and Meng Liu. Their work appears in journals such as Knowledge-Based Systems, Information Sciences, Expert Systems with Applications, ACM Transactions on Multimedia Computing Communications and Applications and IEEE Transactions on Neural Networks and Learning Systems.

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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