Deep Remote Sensing Object Detection for Smart City Applications

Remote sensing has become increasingly popular in various fields, including the military, urban planning, and agriculture. This study addresses vehicle detection in smart city development by capturing remote sensing images using a drone platform and creating a new dataset. The experiments successfully confirmed the efficacy of the proposed dataset in the realm of remote sensing vehicle detection research. Comparative experiments of one-stage and two-stage deep object detection methods were systematically conducted to elucidate the strengths and weaknesses of various methodologies employed in the precision and real-time performance of vehicle detection.