eglrp Goto Github PK

randomforeast

包含决策树、随机森林、相关参数调优过程的具体实现代码并通过可视图片形式进行展示

ransac_plane_detection

Application of Random Sample Consensus for detection of planes in a point cloud.

ransacline

rcnn-vehicle-tracking-lane-detection

Vehicle Detection using Mask R-CNN and Computer Vision based Lane Detection

rconjgrad

(Non-linear) Conjugate Gradient Optimizer in R with Rasmussen and More-Thuente Line Search

read_detectron.pytorch

readings

research materials

real-time-stereo

Real Time Stereo code repository

recent_slam_research

跟踪SLAM前沿动态【周更】

redqueen

里面现在有headfirst设计模式，以及一些小技巧

refactoring-cheat-sheet

重构速查表，基于《重构--改善既有代码的设计》

refer_rtk

reference

referance_of_wangdao

14年6月-8月王道培训笔记整理

refinenet

RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

refinenet-image-segmentation

a tensorflow implement of refinenet ,RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

registration

registrationoptimization

Register two point clouds rigidly using closest point distances and levenberg-marquardt to optimize the transform

relative-pose-estimation

Relative pose estimation pack

remote-sensing-and-laser-point-cloud-registration

利用共线方程，将遥感影像和对应的激光点云之间进行配准

remotesensing_mask_rcnn

Building instance segmentation using Mask RCNN

repository

some notes

representative

res_unet

Residual unet

resnet_keras

Reproduce ResNet(50layers) with Keras with Tensorflow backend

resource

retained_undistort_image

Sourcecode to produce undistorted image in which all source image pixels are retained. Two methods are implemented (1) using cv::initUndistortRectifyMap and cv::getOptimalNewCameraMatrix, (2) using the reverse distortion technique with cv::remap to produce the undistorted image.

rewrite-design-pattern

软件设计与架构模式课程作业

rfcn

pytorch recurrent FCN for saliency (RFCN[1])

rfcn_couplenet.pytorch

A Pytorch Implementation of R-FCN/CoupleNet, transfer from https://github.com/princewang1994/R-FCN.pytorch

rgbd-pl-slam

RGBD SLAM with Point and Line Feature. This project is developed based on ORB-SALM.