# Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique Source: [Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique]() Collection index: [llms.txt]() Data updated: 2025-10-25T23:21:36.715Z Authors: Atul Sharma, Bulla Rajesh, Mohammed Javed Published: 2021-07-10T11:10:28.000Z ## Abstract Plant leaf diseases pose a significant danger to food security and they cause depletion in quality and volume of production. Therefore accurate and timely detection of leaf disease is very important to check the loss of the crops and meet the growing food demand of the people. Conventional techniques depend on lab investigation and human skills which are generally costly and inaccessible. Recently, Deep Neural Networks have been exceptionally fruitful in image classification. In this research paper, plant leaf disease detection employing transfer learning is explored in the JPEG compressed domain. Here, the JPEG compressed stream consisting of DCT coefficients is, directly fed into the Neural Network to improve the efficiency of classification. The experimental results on JPEG compressed leaf dataset demonstrate the efficacy of the proposed model. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. ## Original sources and implementation [Original paper]() [PDF]()