A Transfer Learning Approach for Detecting Plant Leaf Diseases With Convolutional Neural Networks

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Author(s): P. Valarmathi (Vellore Institute of Technology, Chennai, India), N. G. Bhuvaneswari Amma (Vellore Institute of Technology, Chennai, India)and Vasu Bhasin (Vellore Institute of Technology, Chennai, India)
Copyright: 2023
Pages: 11
Source title: Machine Learning and Deep Learning for Smart Agriculture and Applications
Source Author(s)/Editor(s): Mohamamd Farukh Hashmi (National Institute of Technology, Warangal, India)and Avinash G. Kesakr (Visvesvaraya National Institute of Technology, India)
DOI: 10.4018/978-1-6684-9975-7.ch011

Keywords: Agricultural and Food Sciences / Engineering Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

Agriculture is an indispensable sector for the continuity of homo sapiens. In the Indian context where agriculture contributes 19.9 percent of GDP and engages almost 54.6 percent of the population, it requires great measures to be taken to avoid plant diseases. Plant diseases are difficult to track manually as that requires a lot of work and proficiency in plant diseases. It is mandatory to keep a check on at varying phases of crop development to recognize the disease at time. Digitalization as well as adopting technology is essential for agriculture and for the welfare of the farmer. This chapter concentrates on detecting plant diseases using convolutional neural network. The concept of transfer learning is used for classification. The proposed framework can identify various types of diseases efficiently.

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A Transfer Learning Approach for Detecting Plant Leaf Diseases With Convolutional Neural Networks

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