Distinguishing Between Drones and Birds Using CNNs Algorithm

Abstract

Recognizing drones or unmanned aerial vehicles (UAVs) from birds is a crucial capability for numerous applications. We create a convolutional neural network (CNN) drone identification system that can distinguish between images of drones and birds. A dataset of photos taken of birds and drones in various settings is used to train the CNN model. Our model distinguishes between drones and birds with 93% accuracy. The excellent results show that CNNs are capable of accurately differentiating between drones and birds under practical circumstances. Overall, this work demonstrates that deep learning may be used to achieve accurate drone recognition when similar avian items are present.