深度学习在目标检测的研究综述
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TP391.4;TP183

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A Survey of Deep Learning in Target Detection
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    摘要:

    现如今计算机视觉领域的研究热点之一是目标检测,其根本是对图像中指定目标的识别。而深度学习是目前发展快速,应用广泛的一种技术,其具备的学习能力可以在目标检测中对目标进行图像识别、特征提取以及分类识别等操作。通过介绍深度学习的研究进展、分析了各种网络模型的特点。最后总结了深度学习在目标检测领域的应用发展,结合当前问题和挑战,分析了以后的研究发展。

    Abstract:

    Nowadays, one of the research focuses in the field of computer vision is target detection, which aims at identifying and detecting the designated targets in images. At present, deep learning is a technology with rapid development and wide application range, and its learning ability can perform image recognition, feature extraction, classification recognition and other operations in target detection. This paper mainly introduces the research progress of deep learning and analyzes the characteristics of various network models.Finally,the paper expounds the application development of deep learning in the field of target detection, and analyzes the future research development is combined with the current problems and challenges.

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引用本文

赵立新,邢润哲,白银光,等. 深度学习在目标检测的研究综述[J]. 科学技术与工程, 2021, 21(30): 12787-12795.
Zhao Lixin, Xing Runzhe, Bai Yinguang, et al. A Survey of Deep Learning in Target Detection[J]. Science Technology and Engineering,2021,21(30):12787-12795.

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  • 收稿日期:2021-05-04
  • 最后修改日期:2021-08-16
  • 录用日期:2021-05-28
  • 在线发布日期: 2021-11-10
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