A novel plant disease diagnosis framework by integrating semi-supervised and ensemble learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Horticulture,Plant Science,Agronomy and Crop Science
Link
https://link.springer.com/content/pdf/10.1007/s41348-023-00803-y.pdf
Reference53 articles.
1. Abade A, de Almeida A, Vidal F (2019) Plant diseases recognition from digital images using multichannel Convolutional Neural Networks. In: Proceedings of the 14th international joint conference on computer vision, imaging and computer graphics theory and applications. https://doi.org/10.5220/0007383904500458
2. Ahmad M, Abdullah M, Moon H, Han D (2021) Plant disease detection in imbalanced datasets using efficient convolutional neural networks with stepwise transfer learning. IEEE Access 9:140565–140580. https://doi.org/10.1109/access.2021.3119655
3. Alruwaili M, El-Ghany SA, Shehab A (2019) An enhanced plant disease classifier model based on Deep Learning Techniques. Int J Eng Adv Technol 9:7159–7164. https://doi.org/10.35940/ijeat.a1907.109119
4. Argüeso D, Picon A, Irusta U et al (2020) Few-shot learning approach for plant disease classification using images taken in the field. Comput Electr Agric 175:105542. https://doi.org/10.1016/j.compag.2020.105542
5. Arunnehru J, Vidhyasagar BS, Anwar Basha H (2020) Plant leaf diseases recognition using convolutional neural network and transfer learning. Lecture Notes in Electrical Engineering, pp 221–229. https://doi.org/10.1007/978-981-15-2612-1_21
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