Agriculture is one of the most prominent sources in contemporary society. In agriculture, different crops are yielded in every region of the world to substantially expand the country’s income and production and provide surplus sustenance to people. However, factors like weeds, pests, diseases, and other things may have an extreme impact on the development and crop yield. Due to these factors, farmers struggle to monitor the crop and timely detect crop damage. This review focuses on detecting crop pests and diseases using cutting-edge technologies such as image processing, machine learning, and deep learning. These technologies have shown significant promise to transform numerous sectors due to their robustness for feature learning on enormous image datasets. Moreover, these technologies have given accurate results based on image datasets to detect crop pests and diseases, which is helpful to farmers in implementing remedies.

Crop Pests and diseases, Image Processing, Machine Learning, Deep Learning, Performance Metrics, classification algorithms