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@article{157612,
        author = {Chaitanya Jumale and Pranay Siroya and Shreyansh Sohane and Deepti Barhate},
        title = {Review Paper on Plant Recognition Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {8},
        pages = {862-869},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=157612},
        abstract = {Identification of plants is a crucial issue, particularly for biologists, chemists, and environmentalists. Manually conducted by human specialists, plant identification is a time-consuming and inefficient operation. Automation of plant identification is a crucial step for plant-related fields. In this research we studied methods for plant identification based on leaf photos.[1] Shape and colour data taken from leaf photos are utilised by various machine learning techniques such as k-Nearest Neighbor, Support Vector Machines, Naive Bayes, and Random Forest classification algorithms, etc., to identify plant species.[2] The proposed framework comprises acquiring image, pre-processing, feature extraction, and classification.[1] The experiments are carried out on the Swedish Dataset, the Flavia dataset and the ICL dataset that contains 1800 images belonging to twenty different plant species. },
        keywords = {Leaf recognition, machine learning, image dataset},
        month = {},
        }