Multi-Stage Classification of Pomegranate Anthracnose Disease Severity Levels with CNN and SVM

• Published in: 2023 4th International Conference on Smart Electronics and Communication (ICOSEC) pp. 1117 - 1121
• Main Authors: Thakur, Sahil, Malik, Dhruv, Kukreja, Vinay, Sharma, Rishabh, Yadav, Rishika, Joshi, Kireet
• Format: Conference Proceeding
• Language: English
• Published: IEEE 20.09.2023
• Subjects: Agriculture; Anthracnose disease; Convolutional Neural Network; Convolutional neural networks; Crops; Electric potential; Machine learning; Neural networks; Pomegranate; Severity levels; Support vector machines; Task analysis

This study applies a Convolutional Neural Network (CNN) model along with Support Vector Machines (SVM) to categorize the degrees of anthracnose disease severity. Various crops are susceptible to the fungal disease anthracnose, which results in severe damage and decreased yield. 88.93% overall accura...