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.
Article Details
Unique Paper ID: 157612

Publication Volume & Issue: Volume 9, Issue 8

Page(s): 862 - 869
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