A STUDY OF PLANT DISEASE DETECTION AND CLASSIFICATION BY DEEP LEARNING APPROACHES - SandhyaRani , D; Shyamala, K (Proceedings of the International Conference on Agriculture, 2023)
Agriculture is an important sector in India. In developing countries like India, employment opportunities are provided on large scale. Agriculture comprises many crops and nearly 70% of the population is depending on agriculture. In this study, we have collected more than 30 papers that are published on plant leaf disease identification and classification using Deep Learning algorithms. Plant leaf disease can be occurred by various factors like bacteria, viruses and fungi etc. Identifying the infected leaves is a demanding task for a farmer and also for a researcher. Nowadays, farmers are using pesticides on plants, as a result, it affects human health directly or indirectly and it causes economical loss. Plant Disease Detection techniques are used by the researchers in order to prevent it and the disease will be identified on time. This study will be a helpful resource for the researchers to identify the specific type of plant leaf diseases through deep learning techniques. This paper presents a detailed survey on different papers of various plant leaf diseases depending upon some important criteria like the number of classes (diseases and healthy), size of image dataset, pre-processing, image segmentation, types of classifiers, the accuracy of classifiers, etc