基于深度学习的目标检测技术综述

Utkarsh Namdev, Shikha Agrawal, R. Pandey
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引用次数: 0

摘要

对象检测是一种计算机技术,它在数字图像和视频中搜索特定类别(如人、建筑和汽车)中出现的有意义的主题。它与计算机视觉和图像处理有关。人脸识别和行人识别是识别技术的两个重要方面。目标检测在广泛的视觉识别任务中非常有用,包括图像检索和视频监控。目标检测算法经过多次改进,在速度和精度方面都得到了提升。“由于许多研究人员的不懈努力,深度学习算法正在迅速提高其目标检测性能。行人检测、医学成像、机器人、自动驾驶汽车、人脸识别和其他流行的应用减少了许多领域的劳动力。”它被广泛用于各种行业,应用范围从个人保护到企业生产力。它是驾驶辅助系统和无人驾驶汽车的基本组成部分,可以让汽车识别车道和行人,以避免任何事故。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Object Detection Techniques based on Deep Learning: A Review
Object detection is a computer technique that searches digital images and videos for occurrences of meaningful subjects in particular categories (such as people, buildings, and automobiles). It is related to computer vision and image processing. Two well-studied aspects of identification are facial and pedestrian detection. Object detection is useful in a wide range of visual recognition tasks, including image retrieval and video monitoring. The object detection algorithm has been improved many times to improve the performance in terms of speed and accuracy. “Due to the tireless efforts of many researchers, deep learning algorithms are rapidly improving their object detection performance. Pedestrian detection, medical imaging, robotics, self-driving cars, face recognition and other popular applications have reduced labor in many areas.” It is used in a wide variety of industries, with applications range from individual safeguarding to business productivity. It is a fundamental component of driver assist systems and driverless cars, which allows automobiles to identify driving lanes and pedestrians to avoid any accidents.
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