Plants diseases detection using Convolutional Neural Network and Visual Cryptography


Academic Paper, 2023

7 Pages, Grade: A


Abstract or Introduction

Cotton plant diseases location is a tremendous issue and frequently needs proficient support to identify the infection.

This exploration center's on making a profound learning model that distinguishes the sort of sickness that impacted the plant from the pictures of the leaves of the plants. The profound learning is finished with the assistance of Convolutional Brain Organization by performing move learning.

This technique accomplished condition of workmanship results for the dataset utilized. The primary objective is to bring down the expert assistance to identify the cotton plant illnesses and make this model open to however many individuals as could reasonably be expected. Fast upgrades in profound learning (DL) procedures have made it conceivable to identify and perceive objects from pictures. DL approaches have as of late entered different horticultural and cultivating applications, subsequent to being effectively utilized in different fields.

Details

Title
Plants diseases detection using Convolutional Neural Network and Visual Cryptography
College
Savitribai Phule Pune University, formerly University of Pune
Grade
A
Authors
Year
2023
Pages
7
Catalog Number
V1341545
ISBN (eBook)
9783346856524
Language
English
Keywords
Cotton Plant Diseases, Image Processing, Deep CNN, Deep Learning, Image Recognition
Quote paper
Nilesh Thorat (Author)Dnyandeo Khemnar (Author)Vijay Rathod (Author)Mangesh Salunkhe (Author)Vishal Patil (Author), 2023, Plants diseases detection using Convolutional Neural Network and Visual Cryptography, Munich, GRIN Verlag, https://www.grin.com/document/1341545

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