Deep Learning for Unmanned Aerial Vehicle-Based Object Detection and Tracking: A survey
Глубокое обучение для обнаружения и отслеживания объектов с использованием беспилотных летательных аппаратов: обзор
2021-11-04
SCID: 54.1/h295qynk
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UAV-based object detectioncomputer visiondeep learningobject trackingremote sensing
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Abstract (AI)
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.
Key Findings
1
Deep learning has enabled the broad application of advanced object detection and tracking methods to UAV-related tasks.
2
The paper surveys deep learning methods for object detection and tracking using unmanned aerial vehicle imagery.
3
UAV-based deep learning approaches support applications including environmental monitoring, precision agriculture, and traffic management.
4
UAVs provide effective and flexible data acquisition, making them increasingly important in computer vision and remote sensing.
Research Object
UAV-based object detection and tracking systems
Research Subject
deep-learning methods and their applications for object detection and tracking in UAV imagery
Publication Details
Publication Date
2021-11-04
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