Displaying 1 to 5 from 5 results

cnn-models - ImageNet pre-trained models with batch normalization for the Caffe framework

  •    Python

This repository contains convolutional neural network (CNN) models trained on ImageNet by Marcel Simon at the Computer Vision Group Jena (CVGJ) using the Caffe framework as published in the accompanying technical report. Each model is in a separate subfolder and contains everything needed to reproduce the results. This repository focuses currently contains the batch-normalization-variants of AlexNet and VGG19 as well as the training code for Residual Networks (Resnet). No mean subtraction is required for the pre-trained models! We have a batch-normalization layer which basically does the same.

ResNetCAM-keras - Keras implementation of a ResNet-CAM model

  •    Python

The original Matlab implementation and paper (for AlexNet, GoogLeNet, and VGG16) can be found here. A Keras implementation of VGG-CAM can be found here. This implementation is written in Keras and uses ResNet-50, which was not explored in the original paper.




tensorflow-convolution-models

  •    Jupyter

This repo also contains a notebook that shows the result of the different steps in the convolutional architectures.