def shufflenet_v2_x1_0(**kwargs): planes = [116, 232, 464] layers = [4, 8, 4] model = ShuffleNetV2(planes, layers, 1) return model def shufflenet_v2_x0_5(**kwargs): planes = [48, 96, 192] layers = [4, 8, 4] model = ShuffleNetV2(planes, layers, 1) return model if ...
MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning PDF: https://arxiv.org/pdf/2110.15352.pdf PyTorch代码: https:///shanglianlm0525/CvPytorch PyTorch代码: https:///shanglianlm0525/PyTorch-Networks 1 概述 MCUNetV2取得了...
1 概述 先看下MobileNeXt和MobileNetV2的在ImageNet上的分类性能比较, 明显看出MobileNeXt的优势还是比较明显的. 2 Sandglass Block 下图为ResNet, MobileNetV2和提出的MobileNeXt的对比: ResNet残差块组成:1x1卷积(降维)、3x3卷积(空间信息变换)、1x1卷积(升维) MobileNetV2倒置残差块组成:1x1卷积(升维)、3x3深度可分...
Depthwise Separable Convolution结构 PyTorch实现: AI检测代码解析 import torch import torch.nn as nn import torchvision def BottleneckV1(in_channels, out_channels, stride): return nn.Sequential( nn.Conv2d(in_channels=in_channels,out_channels=in_channels,kernel_size=3,stride=stride,padding=1,groups=...