International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Automated Plant Leaf Classification and Characteristics by Using Machine Learning |
|---|---|
| ABSTRACT | The accurate identification and classification of plant species are fundamental to advancements in agriculture, botany, and pharmacology. Manual identification methods are often time-consuming, prone to human error, and require extensive botanical expertise. This project presents an automated system for plant leaf classification and characteristic analysis by leveraging machine learning and computer vision techniques. Experimental results demonstrate that the proposed model achieves high classification accuracy and robustness against varying environmental conditions. This automated approach provides a scalable and efficient solution for researchers, farmers, and automated agricultural systems, significantly reducing the dependency on manual visual inspection. |
| AUTHOR | R.SRUTHI, DR V SRIRAMA MURTHY, DR T.V.S SRIRAM PG Student, Dept. of MCA, Nadimipalli Satyanarayana Raju Institute of Technology (NSRIT), Visakhapatnam, Andhra Pradesh, India Professor, Dept. of MCA, Nadimipalli Satynarayana Raju Institute of Technology (NSRIT), Visakhapatnam, Andhra Pradesh, India Professor & HOD, Dept. of MCA, Nadimipalli Satynarayana Raju Institute of Technology (NSRIT), Visakhapatnam, Andhra Pradesh, India |
| VOLUME | 186 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1407020 |
| pdf/20_Automated Plant Leaf Classification and Characteristics by Using Machine Learning.pdf | |
| KEYWORDS | |
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