Plant Disease Detection System On Chilli Using Deep Learning Technique
Rathod Mohit
, Gohel Milan
These A vital crop that is grown extensively and has substantial economic value in many regions of the world is chili. Chili plants, however, are extremely vulnerable to a number of illnesses that have a negative impact on yield and quality. Because they require expert involvement, traditional disease identification procedures are labour-intensive, manual, and frequently wrong. A deep learning-based plant disease detection system created especially for chilli plants is presented in this study. Convolutional Neural Networks (CNNs) are used by the system to automatically identify and categorize common chili leaf diseases from digital photos, including Leaf Curl, Anthracnose, and Powdery Mildew.
"Plant Disease Detection System On Chilli Using Deep Learning Technique", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.12, Issue 4, page no.a165-a167, April-2025, Available :https://tijer.org/TIJER/papers/TIJER2504025.pdf
Volume 12
Issue 4,
April-2025
Pages : a165-a167
Paper Reg. ID: TIJER_157317
Published Paper Id: TIJER2504025
Downloads: 000282
Research Area: Science and Technology
Country: rajkot, Gujarat, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
