Leaf Disease Detection Using Transfer Learning
MRS. SWATI R. KHOKALE
, ATHARVA BHALSING , DIPAK BAGUL , AKSHATA UGALE , NIKITA BORSE
Detection, Transfer Learning, CNN, Disease
A deep neural network is very successful for image classification problems. In this project, we show how a neural network can be used for leaf disease detection in the context of image classification. We have used publicly available Plant leaves with our dataset which has different classes of diseases. Hence, the problem that we have addressed is a multi-class classification problem. We are using the Inception V3 architecture and Convolutional Neural Network (CNN) algorithm as a base with Transfer Learning for image processing. With the help of Transfer Learning, we reduce a large amount of time we required for data training and also it increases the accuracy of image recognition
"Leaf Disease Detection Using Transfer Learning", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 5, page no.59 - 63, May-2022, Available :https://ijsdr.org/papers/IJSDR2205011.pdf
Volume 7
Issue 5,
May-2022
Pages : 59 - 63
Paper Reg. ID: IJSDR_200342
Published Paper Id: IJSDR2205011
Downloads: 000347243
Research Area: Engineering
Country: -, -, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
