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3dcnn.torch

Volumetric CNN for feature extraction and object classification on 3D data.

500lines

500 Lines or Less

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

arduino

open-source electronics prototyping platform

auty

基于python2的自动化测试框架

awesome-video-understanding

video-understanding:Video Classification, Action Recognition, Video Datasets

bjtu_thesis

blockly

The web-based visual programming editor.

boxz

BOXZ is is an open source robot platform for DIY interactive entertainments!

c9-python-getting-started

Sample code for Channel 9 Python for Beginners course

caffe-tensorflow

Caffe models in TensorFlow

caffebvlcplus

Caffe: a fast open framework for deep learning.

charliewebdemo

Build a web project demo of SpringMVC and Mybatis by using IDEA with maven.

cloudpoint2deprgb

cloud point to depth and rgb image

cnn_graph

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

coding-web-egret

It is the first time for me to code wbesite of Egret company so that I need to memorize it the important time.

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

cvpr2016_handposeestimation

Robust 3D Hand Pose Estimation in Single Depth Images: from Single-View CNN to Multi-View CNNs

cyaron

CYaRon: Yet Another Random Olympic-iNformatics test data generator

deep-learning-pointnet-project

Classification and Segmentation of the MNIST dataset given as a point set input. Classification: the program classifies hand written digits, given as a sample of 100 points in a 2 dimensional field. the architecture is based on a Stanford article of a PointNet which is especially efficient for 3D image classification. the PointNet classification accuracy is 92.86% Segmentation: this is an extension to the classification net which can later define segments within the pointset. the program receives an input of a handwritten digit, given as a sample of 200 points in a 2 dimensional field, where 100 of the points are a sample of the digit itself, and the rest of the points are "background" points which are not part of the digit. the program classifies each point into one of the 2 segments and returns if it is part of the digit or part of the background. the PointNet segmentation accuracy is 97.65%

detectozord

utilizing PointNet+ PCL for object detection, classification and pose estimation from point clouds

docker-library

kubernetes 相关 images 同步

doraemon

Doraemon-接口自动化测试工具

dxy-covid-19-data

2019新型冠状病毒疫情时间序列数据仓库 | COVID-19/2019-nCoV Infection Time Series Data Warehouse

fast-rcnn

Fast R-CNN

fastfusion

Volumetric 3D Mapping in Real-Time on a CPU

fastslam

FastSLAM with GUI

fcn-colorlabel

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

fcn.tensorflow

Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)