Te-Lin Wu
Impact in
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- Ginger and Zingiberaceae research
Papers in
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- Multimodal Machine Learning Applications 5
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- Topic Modeling 3
- Natural Language Processing Techniques 2
- Co-authors
- Nanyun Peng (7 shared papers)Rujun Han (1 shared paper)Hong Chen (1 shared paper)Hideki Nakayama (1 shared paper)Zhongyi Chen (1 shared paper)Ralph Weischedel (2 shared papers)Pegah Alipoormolabashi (1 shared paper)Marjorie Freedman (2 shared papers)
- Journals
- Journal of Systematics and Evolution (3 papers)Novon A Journal for Botanical Nomenclature (1 paper)Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (1 paper)
- Partner nations
- United StatesIranUnited Kingdom
In The Last Decade
Te-Lin Wu
10 papers receiving 45 citations
Peers
Comparison fields: 5 of 17
- Forestry 4
- Pharmacology 8
- Computer Vision and Pattern Recognition 14
- Ecology, Evolution, Behavior and Systematics 12
- Artificial Intelligence 16
Countries citing papers authored by Te-Lin Wu
This map shows the geographic impact of Te-Lin Wu'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 Te-Lin Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Te-Lin Wu more than expected).
Fields of papers citing papers by Te-Lin Wu
This network shows the impact of papers produced by Te-Lin Wu. 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 Te-Lin Wu. The network helps show where Te-Lin Wu may publish in the future.
Co-authors
The 18 scholars most cited alongside Te-Lin Wu, 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 | 1997 | 15 | |
| 2 | 2022 | 11 | |
| 3 | Lowiaceae, a Family New to the Flora of China | 1964 | 7 |
| 4 | 2022 | 5 | |
| 5 | 2023 | 2 | |
| 6 | Pyrgophyllum, a New Genus of Zingiberaceae from China | 1989 | 2 |
| 7 | 2023 | 2 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 1 | |
| 10 | Materils for Chinese Zingiberaceae | 1978 | 1 |
| 11 | 2024 | 0 |
About Te-Lin Wu
Te-Lin Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Pharmacology, Molecular Biology and Pharmacology, having authored 11 papers that have together received 48 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (5 papers), Topic Modeling (3 papers), Ginger and Zingiberaceae research (3 papers), Natural Language Processing Techniques (2 papers), Plant and Fungal Species Descriptions (2 papers), Pharmacological Effects of Medicinal Plants (1 paper), Online Learning and Analytics (1 paper) and Nephrotoxicity and Medicinal Plants (1 paper). The work is most often cited by research in Forestry (4 citations), Pharmacology (8 citations), Computer Vision and Pattern Recognition (14 citations), Ecology, Evolution, Behavior and Systematics (12 citations) and Artificial Intelligence (16 citations). Te-Lin Wu has collaborated with scholars based in United States, Iran and United Kingdom. Frequent co-authors include Nanyun Peng, Rujun Han, Hong Chen, Hideki Nakayama, Zhongyi Chen, Ralph Weischedel, Pegah Alipoormolabashi, Marjorie Freedman, Pedro Rodríguez and Qingyuan Hu. Their work appears in journals such as Journal of Systematics and Evolution, Novon A Journal for Botanical Nomenclature and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
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.