Juan Cao
- Information Systems top 0.2%
- Spam and Phishing Detection 17
- Artificial Intelligence top 0.5%
- Topic Modeling 12
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- Advanced Image and Video Retrieval Techniques 20
- Video Analysis and Summarization 18
- Sociology and Political Science top 0.5%
- Misinformation and Its Impacts 27
- Signal Processing top 2%
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- Remote Sensing in Agriculture 21
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- Climate change impacts on agriculture 17
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- Complex Network Analysis Techniques 12
- Journals
- Remote Sensing (5 papers)Agricultural and Forest Meteorology (5 papers)Earth system science data (4 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Juan Cao
128 papers receiving 5.6k citations
Hit Papers
Peers
Comparison fields: 5 of 179
- Information Systems 1.5k
- Artificial Intelligence 1.8k
- Computer Vision and Pattern Recognition 1.0k
- Sociology and Political Science 2.0k
- Signal Processing 434
Countries citing papers authored by Juan Cao
This map shows the geographic impact of Juan 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 Juan Cao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Juan Cao more than expected).
Fields of papers citing papers by Juan Cao
This network shows the impact of papers produced by Juan 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 Juan Cao. The network helps show where Juan Cao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Juan Cao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2025 | 2 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 11 | |
| 7 | 2023 | 5 | |
| 8 | 2023 | 11 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 4 | |
| 11 | 2023 | 36 | |
| 12 | 2020 | 16 | |
| 13 | 2019 | 26 | |
| 14 | Rumor Detection on Twitter Pertaining to the 2016 U.S. Presidential Election. | 2017 | 2 |
| 15 | MCG-ICT at MediaEval 2016 Verifying Tweets from both Text and Visual Content. | 2016 | 3 |
| 16 | MCG-ICT at MediaEval 2015: Verifying Multimedia Use with a Two-Level Classification Model | 2015 | 11 |
| 17 | 2014 | 5 | |
| 18 | Study on Virtual Reality | 2011 | 1 |
| 19 | Known-Item Search by MCG-ICT-CAS. | 2010 | 1 |
| 20 | TRECVID 2007 Search Tasks by NUS-ICT | 2007 | 6 |
About Juan Cao
Juan Cao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Acoustics and Ultrasonics, having authored 136 papers that have together received 5.7k indexed citations. Recurring topics across this work include Misinformation and Its Impacts (27 papers), Remote Sensing in Agriculture (21 papers), Advanced Image and Video Retrieval Techniques (20 papers), Video Analysis and Summarization (18 papers), Spam and Phishing Detection (17 papers), Climate change impacts on agriculture (17 papers), Topic Modeling (12 papers) and Complex Network Analysis Techniques (12 papers). The work is most often cited by research in Information Systems (1.5k citations), Artificial Intelligence (1.8k citations) and Computer Vision and Pattern Recognition (1.0k citations). Juan Cao has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Yongdong Zhang, Zhiwei Jin, Zhao Zhang, Sheng Tang, Yuchuan Luo, Jiebo Luo, Fulu Tao, Jintao Li, Jichong Han and Han Guo. Their work appears in journals such as Remote Sensing, Agricultural and Forest Meteorology, Earth system science data, IEEE Transactions on Multimedia and Neurocomputing.
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.