ImageNet pre-trained models with batch normalization for the Caffe framework
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Updated
Nov 26, 2017 - Python
ImageNet pre-trained models with batch normalization for the Caffe framework
Visualising predictions of deep neural networks
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
Transfer learning in Caffe: example on how to train CaffeNet on custom dataset
Hand gesture interface for Desktop PC and Raspberry Pi.
Controllable List-wise Ranking for Universal No-reference Image Quality Assessment
A photo album demo featuring search by image using deep learned features
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 is a repository to provide information about some interesting Deep Learning Practice Problems
How to build Caffe on Compute Canada servers. (Beluga and Cedar)
This project contains example of Matlab interface for Caffe (known as Matcaffe). Currently, the example includes
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
Template for caffe project using docker ☕
Caffe is a deep learning framework, install and setup notes to get Caffe, then ImageNet running.
Friendly Caffe Framework Friends(FCFF)
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.
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.
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