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【检测|RCNN系列-2】目标检测算法Fast RCNN（附论文获取方式）

Fast RCNN算法在RCNN之后的SPPNet虽然解决了重复卷积以及固定输入尺寸的问题，但是依然存在其他的问题，而Fast RCNN则具有更快、更强的性能，不仅训练的步骤可以是西安端到端，而且Backbone也是基于VGG16来及进行设计的，在训练速度上比RCNN快了将近9倍，在前向推理的速度上...

【检测|RCNN系列-1】目标检测算法开山之作RCNN（附论文获取方式）

RCNN算法其实RCNN的算法思想依旧是没能抛弃传统检测方法的思想，把检测问题看作为一个特征分类的问题来看待和解决，于是也便诞生了Two-Stage方法，即先提取图像的候选框，然后对候选框内的特征进行提取和分类。算法具体步骤：1、候选框生成：采用Region Proposal来提取图像中的候选框（S...

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RCNN目标检测算法内容详解（依托论文讲解）

作为目标检测的开山鼻祖，对于RCNN的学习一定是有里程碑的意义的，RCNN的横空出世让我们对神经网络有了更深的认识，在CNN识别盛行的年代开创了先河，因此了解RCNN对于我们学习目标检测算法有非常重大的意义。我在学习目标检测算法的时候，发现有些概念总是模糊不清，因为我是直接学习yolo系...

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