2. 深度可分离卷积(Depthwise Separable Convolution) 2.1 Depthwise Convolution 2.2 Pointwise Convolution 优点 在这里插入图片描述 本文作者: slience_me 我看的论文地址:MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications 内容 1. 标准卷积 假设输入为DF×DF×M,输出为输入为DF×DF×...
Architecture — The first layer of the MobileNet is a full convolution, while all following layers are Depthwise Separable Convolutional layers. All the layers are followed by batch normalization and ReLU activations. The final classification layer has a softmax activation. The full architecture...
Depthwise separable convolution (DSC) was proposed to reduce computation especially in convolutional layers by separating one convolution into a spatial convolution and a pointwise convolution. In this paper, we apply DSC to the YOLO network for object detection and propose a faster version of DSC, ...
MobileNetV1 [12] contains a total of 28 layers, among which 13 are depthwise separable convolutional layers. For some of depthwise convolutions, the stride is set to 2 for downsampling, and the prediction results are finally output through the softmax layer. MobileNet also introduces two hyper...
3. The Xception architecture We propose a convolutional neural network architecture based entirely on depthwise separable convolution layers. In effect, we make the following hypothesis: that the map- ping of cross-channels correlations and spatial correlations in the feature maps of convolutional ...
branchesoperatingsuccessivelyonchannelsandthen7and8).The36convolutionallayersarestructuredinto 14modules,allofwhichhavelinearresidualconnections onspace. aroundthem,exceptforthefirstandlastmodules. •Depthwiseseparableconvolutions,whichourproposedInshort,theXceptionarchitectureisalinearstackof architectureisentirelybas...
Data Locality Optimization of Depthwise Separable Convolutions for CNN Inference Accelerators This paper presents a novel framework to maximize the data reusability in the depthwise separable convolutional layers with the Scan execution order of the... HN Wu,CT Huang - Design, Automation &ampampam...
Separable Convolution在Google的Xception[1]以及MobileNet[2]论文中均有描述。它的核心思想是将一个完整的卷积运算分解为两步进行,分别为Depthwise Convolution与Pointwise Convolution。 Depthwise Convolution 同样是上述例子,一个大小为64×64像素、三通道彩色图片首先经过第一次卷积运算,不同之处在于此次的卷积完全是在二...
在深度学习框架(如Tensorflow和Keras)中通常被称为“Separable convolution”的depth separable convolution包括一个depthwise convolution和后接一个pointwise convolution。depthwise convolution就是在输入的每一个通道上独立地实施空间卷积;pointwise卷积就是卷积,将depthwise convolution输出的通道映射到一个新的...
DEPTHWISE SEPARABLE CONVOLUTIONS FOR NEURAL MACHIN 专利名称：DEPTHWISE SEPARABLE CONVOLUTIONS FOR NEURAL MACHINE TRANSLATION 发明人：GOMEZ, Aidan Nicholas,KAISER, Lukasz Mieczyslaw,CHOLLET, Francois 申请号：US2018/033732 申请日：20180521 公开号：WO2018/213840A1 公开日：20181122 专利内容由知识产权出版社提供...