Buildings and Vehicles Discrimination in Drone Images
摘要
The aim of this work is to analyze the performance of Deep Learning algorithms for detecting vehicles and buildings in aerial images. Two algorithms, Faster R-CNN and YOLO, are compared to identify the best performance. The results showed that there is a considerable discrepancy between the two algorithms, both in terms of performance and speed. Faster R-CNN only proved to be superior in terms of training speed, but YOLO achieved the best results.