Deep Learning for Unmanned Aerial Vehicle-Based Object Detection and Tracking ©SHUTTERSTOCK.COM /EAKNARIN JITONG A survey O XIN WU, WEI LI, DANFENG HONG, RAN TAO, AND QIAN DU Digital Object Identifier 10.1109/MGRS.2021.3115137 Date of current version: 4 November 2021 MARCH 2022 IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE wing to effective and flexible data acquisition, unmanned aerial vehicles (UAVs) have recently become a hotspot across the fields of computer vision (CV) and remote sensing (RS). Inspired by the recent success of deep learning (DL), many advanced object detection and tracking approaches have been widely applied to various UAVrelated tasks, such as environmental monitoring, precision agriculture, and traffic management. This article provides a comprehensive survey on the research progress and prospects of DL-based UAV object 0274-6638/22©2022IEEE 91http://www.SHUTTERSTOCK.COM