Disease Detection on Tomato Leaves Using CNN

EasyChair Preprint 15493

Abstract

The ever-increasing population of the world has led to a shortage in raw materials and food resources. Hence, the agricultural sector has turned out to be this dominant and important source for counteracting such constraint. We will give a short overview of published solutions and concentrate on the less complex machine learning model using a traditional CNN designed as our contribution. This model of machine learning can be implemented in mobile phones, and drones and cameras that farmers can use to detect the affected crops on a large scale and take precautions measures not to allow the disease climb up high and impact supply production.Three, the paper uses the analysis of this mechanismand results obtained by model

Keyphrases: Machine Learning and, convolutional neural network and, disease detection

@booklet{EasyChair:15493,
  author    = {Shruti Chaudhari and Mrunmayi Gujar and Snehal Pawar and Gauri Ghule},
  title     = {Disease Detection on Tomato Leaves Using CNN},
  howpublished = {EasyChair Preprint 15493},
  year      = {EasyChair, 2024}}