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
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
MOVED to GitLab: https://gitlab.com/sciloaf/milla 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
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