Long Lin
Impact in
- Artificial Intelligence top 10%
- Privacy-Preserving Technologies in Data
- AI in cancer detection
Papers in
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- Domain Adaptation and Few-Shot Learning 2
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- Web Data Mining and Analysis 1
- Co-authors
- Keping Yu (3 shared papers)Liang Tan (3 shared papers)Xiaofan Cheng (2 shared papers)Mamoun Alazab (1 shared paper)Bo Gu (1 shared paper)Takuro Sato (1 shared paper)Yi Zhang (1 shared paper)Jerry Chun‐Wei Lin (1 shared paper)
- Journals
- IEEE Transactions on Intelligent Transportation Systems (2 papers)IEEE Wireless Communications (1 paper)Computer-Aided Design (1 paper)Proceedings of the VLDB Endowment (1 paper)Journal of Mathematical Inequalities (1 paper)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Long Lin
8 papers receiving 546 citations
Long Lin's Hit Papers
Peers
Comparison fields: 5 of 86
- Business and International Management 16
- Artificial Intelligence 188
- Computer Networks and Communications 122
- Computer Vision and Pattern Recognition 102
- Media Technology 42
Countries citing papers authored by Long Lin
This map shows the geographic impact of Long Lin'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 Long Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Long Lin more than expected).
Fields of papers citing papers by Long Lin
This network shows the impact of papers produced by Long Lin. 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 Long Lin. The network helps show where Long Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Long Lin, 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 | 2020 | 230 | |
| 2 | Deep-Learning-Empowered Breast Cancer Auxiliary Diagnosis for 5GB Remote E-Health Hit paper breakdown → | 2021 | 211 |
| 3 | 2021 | 120 | |
| 4 | 2015 | 8 | |
| 5 | 2012 | 3 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 1 | |
| 8 | 2021 | 1 | |
| 9 | 2023 | 0 | |
| 10 | 2020 | 0 |
About Long Lin
Long Lin is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Building and Construction and Electrical and Electronic Engineering, having authored 10 papers that have together received 576 indexed citations. Recurring topics across this work include Traffic Prediction and Management Techniques (2 papers), Advanced Data and IoT Technologies (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Multimodal Machine Learning Applications (1 paper), Web Data Mining and Analysis (1 paper), Mathematical functions and polynomials (1 paper), COVID-19 diagnosis using AI (1 paper) and Autonomous Vehicle Technology and Safety (1 paper). The work is most often cited by research in Business and International Management (16 citations), Artificial Intelligence (188 citations), Computer Networks and Communications (122 citations), Computer Vision and Pattern Recognition (102 citations) and Media Technology (42 citations). Long Lin has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Keping Yu, Liang Tan, Xiaofan Cheng, Mamoun Alazab, Bo Gu, Takuro Sato, Yi Zhang, Jerry Chun‐Wei Lin, Gautam Srivastava and Wei Wei. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, IEEE Wireless Communications, Computer-Aided Design, Proceedings of the VLDB Endowment and Journal of Mathematical Inequalities.
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.