MobileNetV3
A lightweight convolutional neural network architecture proposed by Google, optimized specifically for mobile and edge devices, balancing accuracy and inference efficiency.
Timeline (last 90 days)
ResNet-50 and MobileNetV3 are both commonly used ImageNet-pretrained backbone networks; the former has high accuracy, while the latter is suited to edge deployment.
MobileNetV3 采用深度可分离卷积，计算量约为标准卷积的 1/K²+1/C_out，当 K=3 且 C_out=256 时约为原来的 1/8 到 1/9
MobileNetV3 Large 版本在 ImageNet 上达到 75.2% Top-1 精度，推理延迟仅为 ResNet-50 的约 1/5
MobileNetV3 是 Google 针对移动端和边缘设备设计的轻量级架构，采用深度可分离卷积将计算量降低约 8-9 倍，Large 版本在 ImageNet 上达到 75.2% Top-1 精度，推理延迟约为 ResNet-50 的 1/5
All Facts (4)
ResNet-50 and MobileNetV3 are both commonly used ImageNet-pretrained backbone networks; the former has high accuracy, while the latter is suited to edge deployment.
50%UnverifiedMobileNetV3 采用深度可分离卷积，计算量约为标准卷积的 1/K²+1/C_out，当 K=3 且 C_out=256 时约为原来的 1/8 到 1/9
50%UnverifiedMobileNetV3 Large 版本在 ImageNet 上达到 75.2% Top-1 精度，推理延迟仅为 ResNet-50 的约 1/5
50%UnverifiedMobileNetV3 是 Google 针对移动端和边缘设备设计的轻量级架构，采用深度可分离卷积将计算量降低约 8-9 倍，Large 版本在 ImageNet 上达到 75.2% Top-1 精度，推理延迟约为 ResNet-50 的 1/5
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