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

Visualising predictions of deep neural networks

A python script that automatise the training of a CNN, compress it through tensorflow (or ristretto) plugin, and compares the performance of the two networks

Hand gesture interface for Desktop PC and Raspberry Pi.

Transfer learning in Caffe: example on how to train CaffeNet on custom dataset

Controllable List-wise Ranking for Universal No-reference Image Quality Assessment

Softwares tools to predict market movements using convolutional neural networks.

Latte is a convolutional neural network (CNN) inference engine written in C++ and uses AVX to vectorize operations. The engine runs on Windows 10, Linux and macOS Sierra.

Machine Leaning Approaches for Classification of Children with Autism Spectrum Disorder

Image viewer with Computer Vision and Deep Learning: MILLA. A Qt5-based image viewer provides extended functionality for image search, matching, tagging and classification. Rich plugins API makes it possible to run an entire virtual machine inside the viewer.

This is a repository to provide information about some interesting Deep Learning Practice Problems

A Matlab plugin, built on top of Caffe framework, capable of learning deep representations for image classification using the MATLAB interface – matcaffe & various pretrained caffemodel binaries

Repository for studying Caffe deep learning framework.

A photo album demo featuring search by image using deep learned features

Calculates the complexity of a caffe network

Scripts for iterative training with multiple models and datasets using Caffe framework.

Caffe is a deep learning framework, install and setup notes to get Caffe, then ImageNet running.

Java based source-to-source compiler that converts Deep Neural Network model from Caffe Prototxt to TensorFlow. It is heavily inspired by apcahe/incubator-mxnet.

Traffic Light detection with matlab and caffe

Real-time Embedded Deep Learning for Autonomous Lane Change Systems of Autonomous Driving