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15-minute-apps

15 minute (small) desktop apps built with PyQt

30min_guides

覃健祥的学习笔记，各种几十分钟入门的文档

3d-r2n2

Single/multi view image(s) to voxel reconstruction using a recurrent neural network

action-recognition-visual-attention

Action recognition using soft attention based deep recurrent neural networks

affordance-net

AffordanceNet - Multiclass Instance Segmentation Framework

alphapose

annosystem

This is a simple basic tool for Human Keypoints Annotation. Based on cross platform PyQt5.

autocolorize

Automatic colorizaton of grayscale images using Deep Learning

awesome-action-recognition

A curated list of action recognition and related area resources

awesome-scene-text-recognition

A curated list of resources dedicated to scene text localization and recognition

awesome_tensorflow_implementations

awesomeperfcpp

A curated list of awesome C/C++ performance optimization resources: talks, articles, books, libraries, tools, sites, blogs. Inspired by awesome.

bangalore_sentiment

Various NLP methods (in python) to perform sentiment analysis

base-images

bgslibrary

A Background Subtraction Library

blitznet

Deep neural network for object detection and semantic segmentation in real-time. Official code for the paper "BlitzNet: A Real-Time Deep Network for Scene Understanding"

blog

caffe

Caffe on both Linux and Windows

caffe-facialkp

Facial keypoints extraction using Caffe

caffe-model

Python script to generate prototxt on Caffe, specially the inception_v3 \ inception_v4 \ inception_resnet \ fractalnet

caffe-windows

Configure Caffe in one hour for Windows users.

caffe-yolo9000

Caffe for YOLOv2 & YOLO9000

caffe_ocr

主流ocr算法研究实验性的项目，目前实现了CNN+BLSTM+CTC架构

cam-python

Class Activation Mapping with Caffe using the Python wrapper pycaffe instead of matlab.

ccdl

深度学习应用框架，专注于深度学习的工程应用

charades-algorithms

Activity Recognition Algorithms for the Charades Dataset

chencgln.github.io

clandmark

Open Source Landmarking Library

cmake-demo

《CMake入门实战》源码

cnndroid

Open Source Library for GPU-Accelerated Execution of Trained Deep Convolutional Neural Networks on Android