Affiliation:
1. Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, India
2. National Institute of Technology, Uttarakhand, India
Abstract
In the agricultural sector, plant leaf diseases and harmful insects represent a major challenge. Faster and more reliable prediction of leaf diseases in crops may help develop an early treatment technique while reducing economic losses considerably. Current technological advances in deep learning have made it possible for researchers to improve the performance and accuracy of object detection and recognition systems significantly. In this chapter, using images of plant leaves, the authors introduced a deep-learning method with different datasets for detecting leaf diseases in different plants and concerned with a novel approach to plant disease recognition model, based on the classification of the leaf image, by the use of deep convolutional networks. Ultimately, the approach of developing deep learning methods on increasingly large and accessible to the public image datasets provides a viable path towards massive global diagnosis of smartphone-assisted crop disease.
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