Review Paper on Plant Recognition Using Machine Learning
Chaitanya Jumale, Pranay Siroya, Shreyansh Sohane, Deepti Barhate
Leaf recognition, machine learning, image dataset
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.
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Unique Paper ID: 157612

Publication Volume & Issue: Volume 9, Issue 8

Page(s): 862 - 869
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