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

Visualising predictions of deep neural networks

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

Softwares tools to predict market movements using convolutional 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

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

Hand gesture interface for Desktop PC and Raspberry Pi.

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

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

Machine Leaning Approaches for Classification of Children with Autism Spectrum Disorder

Face Recognition in Caffe using different VGGNet architectures on ColorFeret and LFW datasets

This project contains example of Matlab interface for Caffe (known as Matcaffe). Currently, the example includes

Template for caffe project using docker ☕

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

Deploy Neural network visualizer and analyzer locally on local linux

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.

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

How to build Caffe on Compute Canada servers. (Beluga and Cedar)

Face detection, and recognition using MTCNN,FACENET, HAAR CASCADES and CAFFE MODELS