Da Cao

1.6k citations
42 papers · 1.0k indexed · h-index 16

Impact in

Papers in

Da Cao

40 papers receiving 1.0k citations

Peers

Da Cao
Comparison fields: 5 of 84
  • Computer Vision and Pattern Recognition 488
  • Information Systems 449
  • Computer Science Applications 85
  • Artificial Intelligence 491
  • Computational Mathematics 5
Replace Xiaoxuan Shen with:
Xiaoxuan Shen China
Alper Bilge Türkiye
Pipei Huang China
Heung-Nam Kim Canada
Yinwei Wei China
Kan Li China
Minsuk Kahng United States
Roelof van Zwol United States
Xiangyu Song China
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 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018181
2 2020102
3 201792
4 201982
5 201779
6 202160
7 201947
8 201942
9 201841
10 201632
11 202026
12 201925
13 202023
14 201921
15 202220
16 202019
17 201815
18 201914
19 201913
20 202212

About Da Cao

Da Cao is a scholar working on Computer Vision and Pattern Recognition, Computer Science Applications, Artificial Intelligence, Information Systems and Law, having authored 42 papers that have together received 1.0k indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (20 papers), Advanced Image and Video Retrieval Techniques (13 papers), Video Analysis and Summarization (11 papers), Recommender Systems and Techniques (8 papers), Topic Modeling (7 papers), Online Learning and Analytics (5 papers), Domain Adaptation and Few-Shot Learning (5 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (488 citations), Information Systems (449 citations), Computer Science Applications (85 citations), Artificial Intelligence (491 citations) and Computational Mathematics (5 citations). Da Cao has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Liqiang Nie, Xiangnan He, Xiaochi Wei, Richang Hong, Chao Yang, Tat‐Seng Chua, Yahui An, Yawen Zeng, Qi Tian and Meng Liu. Their work appears in journals such as Knowledge-Based Systems, Information Sciences, Expert Systems with Applications, IEEE Transactions on Neural Networks and Learning Systems and ACM Transactions on Multimedia Computing Communications 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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