Leaf Disease Detection and Remedy Recommendation Using CNN

Registration ID: IJNRD_193460

Published ID: IJNRD2305188

DOI: Click Here to Get

T. Jyothi , N. Venkata Ramanaiah , Y. Sai Charitha , R. Akshaya , SK. Nijam Ahamed

CNN, Leaf Disease , Classification, Deep learning , Remedies.

People's lives and economic wellbeing are influenced by agriculture. In terms of GDP, it employs a large number of people and accounts for a significant portion of it. Crop losses are caused in large part by diseases, which are common and unavoidable. Agricultural yields are reduced each year due to poor disease control, which can have a significant impact on the quality, quantity, and productivity of the crop. There is a great deal of value in detecting leaf disease using an automated method such as image processing. Convolutional Neural Networks (CNNs) are the most commonly used deep learning classification technique. An artificial intelligence (AI) classification system that uses a neural network is referred to as a neural network classification system (NNCCS)

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T. Jyothi, N. Venkata Ramanaiah, Y. Sai Charitha, R. Akshaya, & SK. Nijam Ahamed (May-2023). Leaf Disease Detection and Remedy Recommendation Using CNN . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), b671-b679. https://ijnrd.org/papers/IJNRD2305188.pdf

Volume 8 Issue 5, May-2023

Pages : b671-b679

Paper Reg. ID: IJNRD_193460

Published Paper Id: IJNRD2305188

Downloads: 000121989

Research Area: Electronics & Communication Engg. 

Country: Nellore, Andhrapradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305188.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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