A novel plant disease diagnosis framework by integrating semi-supervised and ensemble learning-Reference-Cited by-同舟云学术

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A novel plant disease diagnosis framework by integrating semi-supervised and ensemble learning

Published:2023-09-28 Issue:1 Volume:131 Page:177-198
ISSN:1861-3829
Container-title:Journal of Plant Diseases and Protection
language:en
Short-container-title:J Plant Dis Prot

Author:

Sharma Parul^ORCID,Sharma Abhilasha

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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