Project Proposal Plant Diseases Detection Subject Name: Advanced Database Topics Subject Code: COMP8157 Section: 6 Group Name: Project Instructor: Dr. Olena Syrotkina Prepared by: Student Name Student ID Paridhi Gondalia
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Project Proposal Plant Diseases Detection Subject Name: Advanced Database Topics Subject Code: COMP8157 Section: 6 Group Name: Project Instructor: Dr. Olena Syrotkina Prepared by: Student Name Student ID Paridhi Gondalia 110071190 Preetkumar Patel 110077059 Keneel Shah 110073464 1
Advanced Database TopicsProblem Statement Usually, farmers or professionals examine the plants with their naked eyes to discover and identify diseases. However, this procedure is time-consuming, costly, and imprecise. The goal is to train Convolutional Neural Networks to recognize specific diseases and species to create a deployable system for plant disease diagnosis. The goal of this project is to use deep convolutional networks to establish a new way of developing a plant disease recognition model based on leaf picture categorization. Motivation for the problem Some diseases have no visible symptoms, or the damage becomes apparent too late to intervene, necessitating a thorough investigation. A plant pathologist must have outstanding observation skills to identify distinctive signs and make reliable plant disease diagnoses. Because amateur gardeners and hobbyists may have more difficulty diagnosing ill plants than a professional plant pathologist, variations in symptoms suggested by diseased plants may lead to an incorrect diagnosis. An automated system that can identify plant illnesses based on the look and visual symptoms of the plant might be extremely useful to both amateur gardeners and skilled professionals as a disease diagnosis verification system. Solution Statement The Convolutional Neural Network will be used to implement our project. The gradient details that will be used to create the saliency image are contai
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