Nati-Tsehaye/Crop-pest-identification

Identifying Ethiopian grasshopper and aphid pests using MobileNetV2 This notebook aims to develop a MobileNetV2 model to identify Ethiopian grasshopper and aphid pests. By using advanced machine learning techniques, this notebbok will assist farmers and agricultural professionals in accurately identifying these pests. Introduction Pest infestation is a significant challenge in agriculture, leading to considerable crop losses. Grasshoppers and aphids are common pests affecting crops in Ethiopia. Early and accurate identification of these pests is crucial for effective pest management. This notebook utilizes MobileNetV2, a lightweight convolutional neural network, to build a mobile application that can identify these pests with high accuracy.