Menglong Yan
Impact in
- Media Technology top 0.2%
- Remote-Sensing Image Classification
- Advanced Image Fusion Techniques
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- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
Papers in
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- Remote-Sensing Image Classification 17
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- Advanced Neural Network Applications 26
- Advanced Image and Video Retrieval Techniques 24
- Video Surveillance and Tracking Methods 7
Menglong Yan
55 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Media Technology 1.4k
- Computer Vision and Pattern Recognition 1.3k
- Atmospheric Science 550
- Environmental Engineering 343
- Ocean Engineering 328
Countries citing papers authored by Menglong Yan
This map shows the geographic impact of Menglong Yan'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 Menglong Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Menglong Yan more than expected).
Fields of papers citing papers by Menglong Yan
This network shows the impact of papers produced by Menglong Yan. 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 Menglong Yan. The network helps show where Menglong Yan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Menglong Yan, 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 | 1 | |
| 2 | 2024 | 7 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 16 | |
| 6 | 2024 | 3 | |
| 7 | 2024 | 20 | |
| 8 | 2023 | 16 | |
| 9 | 2023 | 2 | |
| 10 | 2019 | 68 | |
| 11 | 2019 | 36 | |
| 12 | 2019 | 40 | |
| 13 | 2019 | 52 | |
| 14 | R2CNN++: Multi-Dimensional Attention Based Rotation Invariant Detector with Robust Anchor Strategy. | 2018 | 33 |
| 15 | 2018 | 106 | |
| 16 | 2018 | 83 | |
| 17 | 2018 | 90 | |
| 18 | Change Detection Based on Deep Siamese Convolutional Network for Optical Aerial Images Hit paper breakdown → | 2017 | 453 |
| 19 | 2010 | 1 | |
| 20 | 2010 | 4 |
About Menglong Yan
Menglong Yan is a scholar working on Media Technology, Computer Vision and Pattern Recognition, Environmental Engineering, Geology and Ocean Engineering, having authored 56 papers that have together received 2.6k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (26 papers), Advanced Image and Video Retrieval Techniques (24 papers), Remote-Sensing Image Classification (17 papers), Remote Sensing and LiDAR Applications (10 papers), Distributed and Parallel Computing Systems (7 papers), Video Surveillance and Tracking Methods (7 papers), Automated Road and Building Extraction (5 papers) and Remote Sensing in Agriculture (4 papers). The work is most often cited by research in Media Technology (1.4k citations), Computer Vision and Pattern Recognition (1.3k citations), Atmospheric Science (550 citations), Environmental Engineering (343 citations) and Ocean Engineering (328 citations). Menglong Yan has collaborated with scholars based in China, Austria and Iran. Frequent co-authors include Xian Sun, Kun Fu, Hao Sun, Hongqi Wang, Zhi Guo, Wenhui Diao, Xue Yang, Xiaosong Qiu, Jirui Yang and Guangluan Xu. Their work appears in journals such as IEEE Geoscience and Remote Sensing Letters, Remote Sensing, IEEE Access, Remote Sensing Letters and Electronics.
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.