Mobilenet与SSD [英] Mobilenet vs SSD

问题描述

我对mobilenet和SSD感到困惑.据我所知，mobilenet是用于分类和识别的神经网络，而SSD是用于实现多盒检测器的框架.只有两者的组合才能进行对象检测.因此，移动网络可以与resnet，inception等互换. SSD可以与RCNN互换.我的陈述正确吗?

I have some confusion between mobilenet and SSD. As far as I know, mobilenet is a neural network that is used for classification and recognition whereas the SSD is a framework that is used to realize the multibox detector. Only the combination of both can do object detection. Thus, mobilenet can be interchanged with resnet, inception and so on. SSD can be interchanged with RCNN. Are my statements correct?

推荐答案

这里有两种类型的深度神经网络.基础网络和检测网络. MobileNet，VGG-Net，LeNet以及它们都是基础网络.基础网络提供了用于分类或检测的高级功能.如果在此网络的末端使用完全连接的层，则将具有分类.但是，您可以删除完全连接的层，然后将其替换为检测网络，例如SSD，Faster R-CNN等. 实际上，SSD使用基础网络上的最后一个卷积层来执行检测任务. 就像其他基础网络一样，MobileNet也使用卷积来产生高级功能.

There are two type of deep neural networks here. Base network and detection network. MobileNet, VGG-Net, LeNet and all of them are base networks. Base network provide high level features for classification or detection. If you use a fully connected layer at the end of this networks, you have a classification. But you can remove fully connected layer and replace it with detection networks, like SSD, Faster R-CNN, and so on. In fact, SSD use of last convolutional layer on base networks for detection task. MobileNet just like other base networks use of convolution to produce high level features.

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