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曹明伟,Mingwei Cao's Projects

quantizations icon quantizations

Source code for learning and evaluation different quantzation methods

quickhull icon quickhull

C++ implementation of the 3D QuickHull algorithm

qukf icon qukf

An Eigen-based implementation of an UKF filter, allowing the use of quaternions to filter angles

r-cnn-object-detection icon r-cnn-object-detection

Python-caffe simplified implementation of the R-CNN object detection method. I have taken as a starting point the caffe ipython-notebook available at http://nbviewer.ipython.org/github/BVLC/caffe/blob/master/examples/detection.ipynb . The tutorial requires the use of matlab code for calculating selective search bounding boxes. This make it hard to use and slow. Thus, I have implemented bounding boxes proposal with a pythonized BING that I have implemented in another repository. I have also changed the interaction with the script so that the result is a nicer demo.

r-fcn icon r-fcn

R-FCN: Object Detection via Region-based Fully Convolutional Networks

r4r icon r4r

Reconstruction for recognition library

rabit icon rabit

Reliable Allreduce and Broadcast Interface for distributed machine learning

radical icon radical

Tools for radiometric calibration of consumer RGB(D) cameras

radiometriccalibration icon radiometriccalibration

Implementation of the [Lin et al. CVPR'04] paper on radiometric calibration from a single image.

raisr icon raisr

##RAISR: Rapid and Accurate Image Super Resolution (Google)##

random-forest icon random-forest

Randomized Decision Trees: A Fast C++ Implementation of Random Forests.

random-forest-matlab icon random-forest-matlab

A Random Forest implementation for MATLAB. Supports arbitrary weak learners that you can define.

random_forests icon random_forests

This is a very efficient Random Forests implementation for MATLAB based on low level "cart" tree implementation.

randomforest icon randomforest

Simple classification algorithm implemented by C++. 3% error on MNIST dataset

randomrnn icon randomrnn

Contains C++ class of a self-organizing RNN by Lazar et al. (2009)

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