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All issues Volume 79 (2025) ITM Web Conf., 79 (2025) 01037 References
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Open Access
Issue
ITM Web Conf.
Volume 79, 2025
International Conference on Knowledge Engineering and Information Systems (KEIS-2025)
Article Number 01037
Number of page(s) 7
DOI https://doi.org/10.1051/itmconf/20257901037
Published online 08 October 2025
  1. Y. Miao, W. Meng, X. Zhou, SerpensGate- YOLOv8: An enhanced YOLOv8 model for accurate plant disease detection. Front. Plant Sci. 15, 1514832 (2025). https://doi.org/10.3389/fpls.2025.1514832 [Google Scholar]
  2. Y. Wang, P. Zhang, S. Tian, Tomato leaf disease detection based on attention mechanism and multiscale feature fusion. Front. Plant Sci. 15, 1382802 (2024). https://doi.org/10.3389/fpls.2024.1382802 [Google Scholar]
  3. K. Joshi, S. Hooda, A. Sharma, H. Sonah, R. Deshmukh, N. Tuteja, S.S. Gill, R. Gill, Precision diagnosis of tomato diseases for sustainable agriculture through deep learning approach with hybrid data augmentation. Curr. Plant Biol. 41, 100437 (2025). https://doi.org/10.1016/j.cpb.2025.100437 [Google Scholar]
  4. R. Mao, Y. Zhang, Z. Wang, X. Hao, T. Zhu, S. Gao, X. Hu, DAE-Mask: A novel deep-learningbased automatic detection model for in-field wheat diseases. Precis. Agric. 25, 785–810 (2024). https://doi.org/10.1007/s11119-023-10093-x [Google Scholar]
  5. P. Indumathi, R. Kumuthaveni, Coati optimized transfer learning with vision transformer model for improving deep learner based plant diseases detection. Int. J. Intell. Eng. Syst. 17, 277–288 (2024). https://doi.org/10.22266/ijies2024.0831.21 [Google Scholar]
  6. A. Singla, A. Nehra, K. Joshi, A. Kumar, N. Tuteja, R.K. Varshney, S.S. Gill, R. Gill, Exploration of machine learning approaches for automated crop disease detection. Curr. Plant Biol. 40, 100382 (2024). https://doi.org/10.1016/j.cpb.2024.100382 [Google Scholar]
  7. H. Sun, R. Fu, X. Wang, Y. Wu, M.A. Al-Absi, Z. Cheng, Q. Chen, Y. Sun, Efficient deep learningbased tomato leaf disease detection through global and local feature fusion. BMC Plant Biol. 25, 311 (2025). https://doi.org/10.1186/s12870-025-06247-w [Google Scholar]
  8. S. Hemalatha, J.J.B. Jayachandran, A multitask learning-based vision transformer for plant disease localization and classification. Int. J. Comput. Intell. Syst. 17, 188 (2024). https://doi.org/10.1007/s44196-024-00597-3 [Google Scholar]
  9. S.U. Khan, A. Alsuhaibani, A. Alabduljabbar, F. Almarshad, Y.N. Altherwy, T. Akram, A review on automated plant disease detection: Motivation, limitations, challenges, and recent advancements for future research. J. King Saud Univ. Comput. Inf. Sci. 37, 34 (2025). https://doi.org/10.1007/s44443-025-00040-3 [Google Scholar]
  10. S. Kalaivani, C. Tharini, T.S. Viswa, K.F. Sara, S.T. Abinaya, ResNet-based classification for leaf disease detection. J. Inst. Eng. India Ser. B 106, 1–14 (2025). https://doi.org/10.1007/s40031-024-01062-7 [Google Scholar]
  11. P. Yadav, P. Singh, Disease detection techniques in plants: Transition from manual to automation, In Proceedings of International Workshop on New Approaches for Multidimensional Signal Processing, Springer, Singapore, December 03 (2022), 93–109 [Google Scholar]
  12. S. Duhan, P. Gulia, N.S. Gill, E. Narwal, RTR_Lite_MobileNetV2: A lightweight and efficient model for plant disease detection and classification. Curr. Plant Biol. 42, 100459 (2025). https://doi.org/10.1016/j.cpb.2025.100459 [Google Scholar]
  13. M. Rezaei, D. Diepeveen, H. Laga, M.G. Jones, F. Sohel, Plant disease recognition in a low data scenario using few-shot learning. Comput. Electron. Agric. 219, 108812 (2024). https://doi.org/10.1016/j.compag.2024.108812 [Google Scholar]
  14. E. Moupojou, F. Retraint, H. Tapamo, M. Nkenlifack, C. Kacfah, A. Tagne, Segment anything model & fully convolutional data description for plant multi-disease detection on field images. IEEE Access 12, 102592–102605 (2024). https://doi.org/10.1109/ACCESS.2024.3433495 [Google Scholar]
  15. X. Jiang, J. Wang, K. Xie, C. Cui, A. Du, X. Shi, W. Yang, R. Zhai, PlantCaFo: An efficient few-shot plant disease recognition method based on foundation models. Plant Phenomics 7, 100024 (2025). https://doi.org/10.1016/j.plaphe.2025.100024 [Google Scholar]
  16. Z. Salman, A. Muhammad, D. Han, Plant disease classification in the wild using vision transformers and mixture of experts. Front. Plant Sci. 16, 1522985 (2025). https://doi.org/10.3389/fpls.2025.1522985 [Google Scholar]

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