A review on detection of plant diseases using deep learning


EOI: 10.11242/viva-tech.01.05.015

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Citation

Jayant Varma, Shivani Shukla, Adnan Wagle, Sunita Naik, "A review on detection of plant diseases using deep learning", VIVA-IJRI Volume 1, Issue 6, Article 15, pp. 1-5, 2023. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

The extensive research conducted across several fields revealed that in spite of so many already existing solutions for agricultural problems the requirement for an advanced and efficient approach rises. Deep learning, a branch of machine learning, requires sophisticated techniques to process images, extract features, and analyse them to produce promising results. Deep learning models are trained using large amounts of labelled data and neural network architectures, allowing the model to learn features directly from the data without the need for manual feature extraction. Agriculture is one of the sectors that could benefit from deep learning technology approaches, as it can facilitate the upgrading of conventional farming techniques with the most cost-effective approach. Advances in agricultural technology have increased annual crop yields worldwide, but preventing crop loss due to disease is a concern. Farmers face the problem of plant diseases and consequent loss of agricultural productivity. Early detection of plant diseases by rectifying the leaves with the help of deep learning can reduce crop losses because necessary measures can be taken.

Keywords

Agriculture, Deep Learning, Detection, Neural Network, Plant Diseases.

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