Crop Disease Classification using Parametric Optimization
Year: 2023
Type: article
Abstract: The agriculture sector is the backbone of the Indian economy, n number of sectors are directly or indirectly dependent on agricultural growth. Along with the environmental variation the crop disease caused by the various insects is the major reason for the crop damage thus causing huge economic losses to the individual farmers as well as the country. To correctly identify the disease of plants individual experts are needed at a very large scale and must have the knowledge of plant taxonomy. In this situation machine learning plays a vital role in the early detection of crop disease and insects, thus the experiment has been performed with the variation in different hyperparameter values of the deep learning pre-trained model ResNET50 and CNN model. With the different hyperparameter values variation the ResNET50 and CNN have shown 97.11 and 93.33 percentage of accuracy.
Authors: Namrata Bhatt, Ravindra Yadav, Garima Jain, Jagriti Singh Thakur
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W4384921904