This study aimed to train algorithms for detecting commercial unmanned aerial vehicles using machine learning techniques. Neural network architectures YOLOv8 and MobileNetV3 were used to detect unmanned aerial vehicles in images and videos. The models used were pre-trained on the ImageNet dataset and then refined on the SimUAV dataset containing images of four types of drones (Parrot A. https://megavitamines.shop/product-category/coconut-supplements/