Paper Title :Leaf Multiple Disease Identification Using DCNN

Author :Sateesh Kumar Sahu, Anurag Sharma, Rupali Chandrakar

Article Citation :Sateesh Kumar Sahu ,Anurag Sharma ,Rupali Chandrakar , (2023 ) " Leaf Multiple Disease Identification Using DCNN " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 74-79, Volume-11,Issue-5

Abstract : Agriculture field has a high impact on our life. Agriculture is the most important sector of our Economy. Proper management leads to a profit in agricultural products. Farmers do not expertise in leaf disease so they produce less production. Plant leaf diseases detection is the important because profit and loss are depending on production. CNN is the solution for leaf disease detection and classification. Main aim of this research is to detect the apple, grape, corn, potato and tomato plants leaf diseases. Plant leaf diseases are monitoring of large fields of crops disease detection, and thus automatically detected some feature of diseases as per that provide medical treatment. Proposed Deep CNN model has been compared with popular transfer learning approach such as VGG16. Plant leaf disease detection has wide range of applications available in various fields such as Biological Research and in Agriculture Institute. Plant leaf disease detection is the one of the required research topic as it may prove benefits in monitoring large fields of crops, and thus automatically detect the symptoms of diseases as soon as they appear on plant leaves. Keyword - CNN, VGG16, Biological Research, Agriculture, Plant leaf disease, crops.

Type : Research paper

Published : Volume-11,Issue-5

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