这篇文章“Squeeze-and-Excitation Networks”是CVPR2018的一篇论文,因为最近看的MnasNet的论文里面提到了SENet里面提出的一个很有用的block,所以又翻出来看了下这篇文章,原论文见 Squeeze-and-Excitation Networks。 下面是对论文的一个简单翻译: 摘要 卷积神经网络(CNN)的核心组成部分是卷积算子,它通过在...
In this section we conduct extensive experiments on the ImageNet 2012 dataset [30] for the purposes: first, to explore the impact of the proposed SE block for the basic networks with different depths and second, to investigate its capacity of integrating with current state-of-the-art network ...
SENet的全称是Squeeze-and-Excitation Networks,中文可以翻译为压缩和激励网络。主要由两部分组成: Squeeze部分。即为压缩部分,原始feature map的维度为HWC,其中H是高度(Height),W是宽度(width),C是通道数(channel)。Squeeze做的事情是把HWC压缩为11C,相当于把HW压缩成一维了,实际中一般是用global average pooling实现...
1、[DL-架构-ResNet系] 007 SENet这个链接是对SETNET的论文Squeeze-and-Excitation Networks翻译 2、taki0112/SENet-Tensorflow,github上有SENet代码实现,基于tensorflow 3、Squeeze-and-Excitation Networks论文
Squeeze-and-Excitation Networks个人理解 通道关系,从这个角度出发作者提出了一种新的网络结构单元,作者称之为“Squeeze-and-Excitation”网络块。作者的定位是通过精确的建模卷积特征各个通道之间的作用关系...敏感性以使得这些有价值的信息在之后的网络层中能够得到利用,而没有什么用的特征信息则被舍弃。为了达到对通道...
一、论文简介 论文地址：[1709.01507] Squeeze-and-Excitation Networks (arxiv.org)代码地址：https:/...
論文標題:Squeeze-and-Excitation Networks 論文作者:Jie Hu Li Shen Gang Sun 論文地址:https://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Squeeze-and-Excitation_Networks_CVPR_2018_paper.pdf SENet官方Caffe實現:https://github.com/hujie-frank/SENet ...
balance between accuracy and complexity. In practice, using an identical ratio throughout a network may not be optimal (due to the distinct roles performed by different layers), so further improvements may be achievable by tuning the ratios to meet the needs of a given base architecture. 翻译...
Squeeze-and-Excitation Networkshttps://arxiv.org/abs/1709.01507 ILSVRC 2017 image classification winnerhttps://github.com/hujie-frank/SENet 本文主要提出了一个新的网络模块 Squeeze-and-Excitation block,作用就是对不同 channel 给予不同的权重, selectively emphasise informative features and suppress less us...