寇大磊;权冀川;张仲伟;

• 1:陆军工程大学指挥控制工程学院
• 2:中国人民解放军68023部队
• 3:中国人民解放军73671部队

摘要(Abstract)：

在R-CNN框架提出后,基于深度学习的目标检测框架逐渐成为主流,可分为基于候选窗口和基于回归两类。近两年来,在Faster R-CNN、YOLO、SSD等经典的基于深度学习目标检测框架的基础上,出现了大量的优秀框架。根据优化方法对近几年提出的框架进行了梳理和总结。在PASCAL_VOC和MS COCO等主流测试集上对目标检测方法的性能及优缺点进行了对比分析。讨论了目标检测领域当前面临的困难与挑战,对可能的发展方向进行了展望。

关键词(KeyWords)： 深度学习;目标检测;卷积神经网络;计算机视觉

Abstract:

Keywords:

基金项目(Foundation):

作者(Author): 寇大磊;权冀川;张仲伟;

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参考文献(References)：

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