Guowei Dai
Impact in
- Analytical Chemistry top 10%
- Spectroscopy and Chemometric Analyses
- Plant Science top 10%
- Smart Agriculture and AI
- Plant Disease Management Techniques
- Leaf Properties and Growth Measurement
- Plant Virus Research Studies
- Date Palm Research Studies
- Greenhouse Technology and Climate Control
Papers in
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- Smart Agriculture and AI 13
- Plant Disease Management Techniques 3
- Plant Virus Research Studies 3
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- AI in cancer detection 3
- Co-authors
- Jingchao Fan (7 shared papers)Christine Dewi (9 shared papers)C. K. Sunil (1 shared paper)Long‐Qing Chen (1 shared paper)Keshav Kaushik (1 shared paper)Qingfeng Tang (4 shared papers)Hu Chen (5 shared papers)Inam Ullah Khan (1 shared paper)
In The Last Decade
Guowei Dai
19 papers receiving 313 citations
Guowei Dai's Hit Papers
Peers
Comparison fields: 5 of 57
- Analytical Chemistry 68
- Plant Science 229
- Computer Vision and Pattern Recognition 38
- Industrial and Manufacturing Engineering 16
- Biophysics 7
Countries citing papers authored by Guowei Dai
This map shows the geographic impact of Guowei Dai'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 Guowei Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guowei Dai more than expected).
Fields of papers citing papers by Guowei Dai
This network shows the impact of papers produced by Guowei Dai. 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 Guowei Dai. The network helps show where Guowei Dai may publish in the future.
Co-authors
The 16 scholars most cited alongside Guowei Dai, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | DFN-PSAN: Multi-level deep information feature fusion extraction network for interpretable plant disease classification Hit paper breakdown → | 2023 | 88 |
| 2 | 2023 | 53 | |
| 3 | 2023 | 42 | |
| 4 | 2022 | 36 | |
| 5 | 2022 | 31 | |
| 6 | 2022 | 28 | |
| 7 | 2023 | 9 | |
| 8 | 2024 | 6 | |
| 9 | 2023 | 5 | |
| 10 | 2024 | 5 | |
| 11 | 2024 | 3 | |
| 12 | 2024 | 2 | |
| 13 | 2025 | 2 | |
| 14 | 2025 | 2 | |
| 15 | 2025 | 2 | |
| 16 | 2024 | 1 | |
| 17 | 2024 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2025 | 0 |
About Guowei Dai
Guowei Dai is a scholar working on Plant Science, Artificial Intelligence, Cell Biology, Analytical Chemistry and Computer Vision and Pattern Recognition, having authored 21 papers that have together received 318 indexed citations. Recurring topics across this work include Smart Agriculture and AI (13 papers), Plant Disease Management Techniques (3 papers), Plant Pathogens and Fungal Diseases (3 papers), Spectroscopy and Chemometric Analyses (3 papers), Plant Virus Research Studies (3 papers), AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Industrial Vision Systems and Defect Detection (2 papers). The work is most often cited by research in Analytical Chemistry (68 citations), Plant Science (229 citations), Computer Vision and Pattern Recognition (38 citations), Industrial and Manufacturing Engineering (16 citations) and Biophysics (7 citations). Guowei Dai has collaborated with scholars based in China, Indonesia and India. Frequent co-authors include Jingchao Fan, Christine Dewi, C. K. Sunil, Long‐Qing Chen, Keshav Kaushik, Qingfeng Tang, Hu Chen, Inam Ullah Khan, Bowen Jin and Jun Li. Their work appears in journals such as Computers and Electronics in Agriculture, Information Fusion, Frontiers in Plant Science, Agronomy and Network Computation in Neural Systems.
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.