Open Access
| Issue |
ITM Web Conf.
Volume 73, 2025
International Workshop on Advanced Applications of Deep Learning in Image Processing (IWADI 2024)
|
|
|---|---|---|
| Article Number | 02026 | |
| Number of page(s) | 8 | |
| Section | Machine Learning, Deep Learning, and Applications | |
| DOI | https://doi.org/10.1051/itmconf/20257302026 | |
| Published online | 17 February 2025 | |
- D. S. Joseph, P. M. Pawar and K. Chakradeo, Real-Time Plant Disease Dataset Development and Detection of Plant Disease Using Deep Learning, in IEEE Access, vol. 12, pp. 16310-16333, (2024) [CrossRef] [Google Scholar]
- Y. Bi, H. Zhu, J. Shi, et al. TsCANet: three-stream contrastive adaptive network for cross-domain few-shot learning. j Supercomput 81, 139 (2024) [Google Scholar]
- A. M. Roy, J. Bhaduri. A Deep Learning Enabled Multi-Class Plant Disease Detection Model Based on Computer Vision. ai, 2, 413-428 (2021) [CrossRef] [Google Scholar]
- P. Gole, P. Bedi, S. Marwaha, et al. TrIncNet: a lightweight vision transformer network for identification of plant diseases. Frontiers in Plant Science, 14, 1221557. (2023) [CrossRef] [Google Scholar]
- P. S. Thakur, S. Chaturvedi, P. Khanna, et al. Vision transformer meets convolutional neural network for plant disease classification. Ecological Informatics, 77, 102245 (2023) [CrossRef] [Google Scholar]
- X. Yang, J. M. Duan, M. G. Dong, et al. A mobile-oriented image recognition method for plant diseases and its application. Jiangsu Agricultural Science, 51(04), 191-197 (2023) [Google Scholar]
- M. Yu, Z. Y. Guo, Y. Wang, et al. A review of computer vision-based plant disease recognition methods. Science, Technology and Engineering, 24(12), 4811-4823 (2024) [Google Scholar]
- D. Q. Zhu, Q. Feng, J. H. Zhang, et al. A plant disease identification method based on pruning. Zhejiang Journal of Agriculture, 35(06), 1462-1472 (2023) [Google Scholar]
- H. P. Yin, B. Chen, Y. Chai, et al. A review of vision-based target detection and tracking. Journal of Automation, 42(10), 1466-1489 (2016) [Google Scholar]
- X. F. Liu, M. Y. Chen, C. L. Li, et al. UAV detection and tracking method based on computer vision technology. Journal of Jinan University (Natural Science Edition), 38(04), 445-455 (2024) [Google Scholar]
- C. Liu, H. F. Mo, C. Ma, et al. Plant disease recognition method based on Transformer and CNN in real scenarios. Modern Computer, 29(11), 22-27 (2023) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.