A Crop Pest Classification Model Using Deep Learning Techniques

This paper provides a pest identification system to classify crops' beneficial and harmful pests. For that purpose, the paper first provides a detailed description of the available pests-identification techniques along with their pros and cons. Based on the investigation, a novel classification technique is proposed in this paper. The proposed pests-identification and classification model has been developed using the Convolutional Neural Network (CNN). The model has been trained with a dataset of 9,500 images of 20 different pests. The system has been tested with a huge amount of data and validated across other traditional classification models. The classification accuracy of the proposed system is measured by 90% that is far more superior to other conventional methods.