DETECTING PLANT LEAF DISEASE THROUGH THE APPLICATION OF DEEP LEARNING ALGORITHMS

DETECTING PLANT LEAF DISEASE THROUGH THE APPLICATION OF DEEP LEARNING ALGORITHMS

Niranjan Murthy M1, Swetha C S2

1Student, Department of MCA, Bangalore Institute of Technology, Karnataka, India

2Professor, Department of MCA, Bangalore Institute of Technology, Karnataka, India

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ABSTRACT: The Plant Disease Detection System make use of deep learning techniques to provide an efficient and scalable solution to find and categorize plant diseases from leaf images. Utilizing a previously trained convolutional neural network (CNN) model, the system achieves high accuracy in identifying various plant diseases, thus aiding in early detection and management. This paper details the implementation process, including system architecture, data flow, and testing methodologies, make sure the system meets the specified functional and non-functional requirements. The outcome indicate the system robustness, usability, and scalability, make it as a important tool for farmers and agricultural experts. Future enhancements include expanding the disease database, real-time monitoring, mobile application development, and integration with agricultural management systems.

Key Words: Plant Disease Detection, Deep Learning, Convolutional Neural Network (CNN), Image Processing, Agricultural Technology, Disease Classification.