Jiaming Lv
Impact in
- Nephrology top 10%
- Gout, Hyperuricemia, Uric Acid
-
- Cancer-related molecular mechanisms research
Papers in
-
- Advanced Fiber Optic Sensors 5
- Magneto-Optical Properties and Applications 2
- Co-authors
- Peihua Li (1 shared paper)Qilong Wang (1 shared paper)Jiangtao Xie (1 shared paper)Fei Long (1 shared paper)Hairong Zhao (7 shared papers)Jidong Cheng (6 shared papers)Qiang Wang (5 shared papers)De Xie (6 shared papers)
- Journals
- Optics Express (2 papers)Scientific Reports (2 papers)Neuropeptides (1 paper)Annals of Palliative Medicine (1 paper)Cell Biology International (1 paper)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Jiaming Lv
28 papers receiving 495 citations
Jiaming Lv's Hit Papers
Peers
Comparison fields: 5 of 102
- Nephrology 44
- Cancer Research 83
- Computer Vision and Pattern Recognition 84
- Artificial Intelligence 123
- Media Technology 25
Countries citing papers authored by Jiaming Lv
This map shows the geographic impact of Jiaming Lv'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 Jiaming Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiaming Lv more than expected).
Fields of papers citing papers by Jiaming Lv
This network shows the impact of papers produced by Jiaming Lv. 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 Jiaming Lv. The network helps show where Jiaming Lv may publish in the future.
Co-authors
The 25 scholars most cited alongside Jiaming Lv, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification Hit paper breakdown → | 2022 | 166 |
| 2 | 2022 | 90 | |
| 3 | 2021 | 35 | |
| 4 | 2021 | 31 | |
| 5 | 2021 | 22 | |
| 6 | 2020 | 22 | |
| 7 | 2020 | 21 | |
| 8 | 2022 | 17 | |
| 9 | 2018 | 15 | |
| 10 | 2022 | 11 | |
| 11 | 2022 | 11 | |
| 12 | 2020 | 10 | |
| 13 | 2024 | 9 | |
| 14 | 2022 | 8 | |
| 15 | 2023 | 6 | |
| 16 | 2024 | 4 | |
| 17 | 2025 | 4 | |
| 18 | 2021 | 4 | |
| 19 | 2025 | 3 | |
| 20 | 2021 | 3 |
About Jiaming Lv
Jiaming Lv is a scholar working on Molecular Biology, Electrical and Electronic Engineering, Pulmonary and Respiratory Medicine, Oncology and Epidemiology, having authored 32 papers that have together received 508 indexed citations. Recurring topics across this work include Advanced Fiber Optic Sensors (5 papers), Forensic and Genetic Research (3 papers), Alzheimer's disease research and treatments (3 papers), High voltage insulation and dielectric phenomena (3 papers), Gout, Hyperuricemia, Uric Acid (3 papers), Cancer-related molecular mechanisms research (3 papers), Forensic Fingerprint Detection Methods (3 papers) and Magneto-Optical Properties and Applications (2 papers). The work is most often cited by research in Nephrology (44 citations), Cancer Research (83 citations), Computer Vision and Pattern Recognition (84 citations), Artificial Intelligence (123 citations) and Media Technology (25 citations). Jiaming Lv has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Peihua Li, Qilong Wang, Jiangtao Xie, Fei Long, Hairong Zhao, Jidong Cheng, Qiang Wang, De Xie, Furong He and Chenxi Xu. Their work appears in journals such as Optics Express, Scientific Reports, Neuropeptides, Annals of Palliative Medicine and Cell Biology International.
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.