Apple Leaf Disease Detection and Classification Using CNN Models
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-2719-5_26
Reference24 articles.
1. Kundu, N., et al.: IoT and interpretable machine learning based framework for disease prediction in pearl millet. Sensors 21(16), 5386 (2021)
2. Kundu, N., Rani, G., Dhaka, V.S.: A comparative analysis of deep learning models applied for disease classification in bell pepper. In: 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC), pp. 243–247 (2020). https://doi.org/10.1109/PDGC50313.2020.9315821
3. Dhaka, V.S., et al.: A survey of deep convolutional neural networks applied for prediction of plant leaf diseases. Sensors 21(14), 4749 (2021)
4. Studies in Big Data;D Sinwar,2020
5. Agarwal, M., Rani, G., Agarwal, S., Dhaka, V.: Sequential model for digital image contrast enhancement. Recent Adv. Comput. Sci. Commun. (2020). https://doi.org/10.2174/2666255813999200717231942
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