Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{164459,
        author = {Neha Malhotra and Dr. Geeta Rani},
        title = {A Review on Plant Leaf Identification and Classification Using Machine Learning Techniques},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {1544-1552},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=164459},
        abstract = {Leaf and plant recognition is a rapidly expanding field of study that has huge practical implications for industries as diverse as agriculture, crop rotation, horticulture and others. Image capture, including leaf image improvement, leaf segmentation, extraction of features, and classification, is the first step in the process. One widespread use of these categories nowadays is in the categorization of plants. Several methods for identifying and categorizing plant leaves are discussed in this paper. With the advent of new technologies like machine learning leaf recognition become easier and accurate. Moreover, comparative analysis of machine and deep learning based techniques for leaf recognition based on factors such as dataset used, features considered, classifier type and accuracy obtained has been executed. Apart from this the open research issues and their suggestive solutions has been highlighted in this paper.},
        keywords = {Machine learning, Deep learning, accuracy, Support vector machine, CNN, Classification, Accuracy.},
        month = {},
        }