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Aaron Fox's Projects

bootstrap icon bootstrap

The most popular front-end framework for developing responsive, mobile first projects on the web.

caffe icon caffe

Caffe: a fast open framework for deep learning.

caffe-segnet icon caffe-segnet

Implementation of SegNet: A Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-Wise Labelling

chatgpt-next-web icon chatgpt-next-web

A well-designed cross-platform ChatGPT UI (Web / PWA / Linux / Win / MacOS). 一键拥有你自己的跨平台 ChatGPT 应用。

cuda-cnn icon cuda-cnn

CNN accelerated by cuda. Test on mnist and finilly get 99.76%

cxxnet icon cxxnet

fast, concise, distributed deep learning framework

deeplearntoolbox icon deeplearntoolbox

Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

from_coder_to_expert icon from_coder_to_expert

2019年最新总结,从程序员到CTO,从专业走向卓越,分享大牛企业内部pdf与PPT

javacnn icon javacnn

A Java implement of Convolutional Neural Network.

mc-cnn icon mc-cnn

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

openpose icon openpose

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

pyml icon pyml

Practice Machine Learning by Python

rcnn icon rcnn

R-CNN: Regions with Convolutional Neural Network Features

scala-dist icon scala-dist

Additional code relevant to creating a scala distribution.

segnet-tutorial icon segnet-tutorial

Files for a tutorial to train SegNet for road scenes using the CamVid dataset

theano icon theano

Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.

tiny-cnn icon tiny-cnn

header only deep learning library in C++11/TBB

www_deep_crowd icon www_deep_crowd

The source code for our CVPR 2015 work "Deeply Learned Attributes for Crowded Scene Understanding" with a two-branch CNN model.

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