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A Mathematical Analysis of Feature Extraction Methodologies with Application on Leaf Disease Detection
  • Akshat Kishore
Akshat Kishore
The Shri Ram School

Corresponding Author:[email protected]

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Abstract

This study compares novel and established feature extraction techniques for classifying leaf diseases. Conventional methods like Transfer Learning and DCT are contrasted with novel techniques like Segmentation using a hetero- geneous data set of healthy and diseased leaf images. With little training data, transfer learning is beneficial, but with large data, more efficient al- gorithms may be more suitable, such as the custom segmentation model described in this work. The development of efficient plant disease detection systems using the information from these discoveries would improve agricul- tural practises and increase food security.