Identification of Banana Leaf Diseases: A Collaboration of Deep Learning Models
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1111-6_25
Reference7 articles.
1. Abdullahil Baki Bhuiyan Md et al. (2023) BananaSqueezeNet: A very fast, lightweight convolutional neural network for the diagnosis of three prominent banana leaf diseases. Smart Agric Technol 4:100214, ISSN 2772-3755. https://doi.org/10.1016/j.atech.2023.100214
2. Raja NB, Rajendran PS (2023) An efficient banana plant leaf disease classification using optimal ensemble deep transfer network. J Exp Theor Artif Intell. https://doi.org/10.1080/0952813X.2023.2241867
3. Sangeetha R (2023) An Improved agro deep learning model for detection of panama wilts disease in banana leaves. AgriEngineering 5(2):660–679. https://doi.org/10.3390/agriengineering5020042
4. Devi MS, Vamshikrishna B, Pandian JA, Rao PV, Yaseen SR (2022) “Eight convolutional layered deep convolutional neural network based banana leaf disease prediction.” In: International conference on computing, communication, and intelligent systems (ICCCIS), Greater Noida, India, pp. 313–317, doi: https://doi.org/10.1109/ICCCIS56430.2022.10037628
5. Solemane Coulibaly et al (2022) Deep learning for precision agriculture: A bibliometric analysis. Intell Syst Appl 16:200102, ISSN 2667-3053. https://doi.org/10.1016/j.iswa.2022.200102
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