IoT and Interpretable Machine Learning Based Framework for Disease Prediction in Pearl Millet

IoT and Interpretable Machine Learning Based Framework for Disease Prediction in Pearl Millet

Decrease in crop yield and degradation in product quality due to plant diseases such as rust and blast in pearl millet is the cause of concern for farmers and the agriculture industry. The stipulation of expert advice for disease identification is also a challenge for the farmers. The traditional te...

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Bibliographic Details
Main Authors: Nidhi Kundu, Geeta Rani, Vijaypal Singh Dhaka, Kalpit Gupta, Siddaiah Chandra Nayak, Sahil Verma, Muhammad Fazal Ijaz, Marcin Woźniak
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Sensors
Subjects:
machine learning
interpretable
context-aware
deep learning
IoT
Online Access:https://www.mdpi.com/1424-8220/21/16/5386

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