Recognizing Bangladeshi Agricultural Insects Using Machine Learning

Abstract

Recently, some work has been done on agricultural insect recognition. But a limited number of works is done on Bangladeshi agricultural insects. Pests decimate crops on a massive scale each year. To achieve high crop output, pest detection and identification are necessary. For efficient pest control management, early pest detection in photographs is absolutely essential. Therefore, it has been difficult to identify the pest in the picture. I gathered the dataset for this study from a variety of sources. To achieve the greatest results in this study, I combined deep learning and transfer learning. I used some Deep Neural Networks here (DNN). ResNet50 and VGG16 produce the greatest results out of all of them. The model's output demonstrated 96.4% accuracy on the testing dataset, which is superior to other previous works. Keywords — Convolutional Neural Network, Transfer Learning, Bangladeshi Agricultural insect Recognition, Bangladeshi Agricultural insects.