We study an algorithm for diagnosing diseases occurring in peppers using deep learning technology based on NAS that automatically discovers artificial neural network architectures. It compares and analyzes the diagnosis result from the algorithm other...
We study an algorithm for diagnosing diseases occurring in peppers using deep learning technology based on NAS that automatically discovers artificial neural network architectures. It compares and analyzes the diagnosis result from the algorithm other than the NAS and the experiment result by applying the disease data to the existing NAS and proposes a new algorithm by further developing the BCSA algorithm. It has been proved that the performance of the classifier can be improved through genetic algorithms and the optimal architecture for diagnosing diseases can be found through genetic algorithms without humans directly adjusting the parameters. It allows you to explore the architecture in space. In this study, an experiment to diagnose pests and pests of crops was conducted based on images, and an accuracy of 99% was achieved.