BertMoons

QuantizedNeuralNetworks-Keras-Tensorflow

Quantized Neural Networks - networks trained for inference at arbitrary low precision.

Comparing-CNN-Architectures

A regularly updated comparison of CNN architectures in terms of accuracy, operations and model size

BinarEye

This is example code on how to train Binary Neural Networks that fit on the BinarEye chip

QuantizedNeuralNetworks-Lasagne-Theano

MobileNet-Caffe

Caffe Implementation of Google's MobileNets (v1 and v2)

caffe-faster-rcnn-resnet-fpn

HRNet-Semantic-Segmentation

This is an official implementation of semantic segmentation for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919

MobileNetV2-pytorch

Impementation of MobileNetV2 in pytorch

MobilenetV3-Caffe

From pytorch-mobilenetv3 to caffe

MobileNetV3-pytorch

Implementation of MobileNetV3 in pytorch

mobilenetv3.pytorch

74.3% MobileNetV3-Large and 67.2% MobileNetV3-Small model on ImageNet

once-for-all

[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment

onnx

Open standard for machine learning interoperability

pytorch-mobilenet-v3

MobileNetV3 in pytorch and ImageNet pretrained models

synopsys-caffe-models

Caffe models for use with Synopsys DesignWare EV6x Processors

vision

Datasets, Transforms and Models specific to Computer Vision