基于深度学习的无人机目标检测与跟踪研究综述

IF 16.2 1区地球科学 Q1 GEOCHEMISTRY & GEOPHYSICS IEEE Geoscience and Remote Sensing Magazine Pub Date : 2021-10-25 DOI:10.1109/MGRS.2021.3115137

Xin Wu, Wei Li, D. Hong, R. Tao, Qian Du

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引用次数: 78

摘要

由于数据采集的有效性和灵活性，无人机最近成为计算机视觉（CV）和遥感（RS）领域的热点。受深度学习（DL）最近成功的启发，许多先进的目标检测和跟踪方法已被广泛应用于各种无人机相关任务，如环境监测、精准农业和交通管理。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Deep Learning for Unmanned Aerial Vehicle-Based Object Detection and Tracking: A survey

Owing 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 UAV-related tasks, such as environmental monitoring, precision agriculture, and traffic management.

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来源期刊

IEEE Geoscience and Remote Sensing Magazine Computer Science-General Computer Science

CiteScore

20.50

自引率

2.70%

发文量

期刊介绍： The IEEE Geoscience and Remote Sensing Magazine (GRSM) serves as an informative platform, keeping readers abreast of activities within the IEEE GRS Society, its technical committees, and chapters. In addition to updating readers on society-related news, GRSM plays a crucial role in educating and informing its audience through various channels. These include:Technical Papers,International Remote Sensing Activities,Contributions on Education Activities,Industrial and University Profiles,Conference News,Book Reviews,Calendar of Important Events.