Black gram disease classification using a novel deep convolutional neural network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-15220-4.pdf
Reference47 articles.
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3. Barbedo JGA (2018) Impact of Dataset size and variety on the effectiveness of deep learning and transfer learning for plant disease classification. Comput Electron Agric 153:46–53. https://doi.org/10.1016/j.compag.2018.08.013
4. Brahimi M, Boukhalfa K, Moussaoui A (2017) Deep learning for tomato diseases: classification and symptoms visualization. Appl Artif Intell 31(4):299–315. https://doi.org/10.1080/08839514.2017.1315516
5. Chen LC, Zhu Y, Papandreou G, Schroff F, Adam H (2018) Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. In: Ferrari V, Hebert M, Sminchisescu C, Weiss Y (eds) Computer vision – ECCV 2018. ECCV 2018. Lecture Notes in Computer Science, vol 11211. Springer, Cham. https://doi.org/10.1007/978-3-030-01234-2_49
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