About: An implementation of MROGH descriptor. For more information, please refer to: “Bin Fan, Fuchao Wu and Zhanyi Hu, Aggregating Gradient Distributions into Intensity Orders: A Novel Local Image Descriptor, CVPR 2011, pp.23772384.” The most uptodate information can be found at : http://vision.ia.ac.cn/Students/bfan/index.htm Changes:Initial Announcement on mloss.org.

About: TurboParser is a free multilingual dependency parser based on linear programming developed by André Martins. It is based on joint work with Noah Smith, Mário Figueiredo, Eric Xing, Pedro Aguiar. Changes:This version introduces a number of new features:
Note: The runtimes above are approximate, and based on experiments with a desktop machine with a Intel Core i7 CPU 3.4 GHz and 8GB RAM. To run this software, you need a standard C++ compiler. This software has the following external dependencies: AD3, a library for approximate MAP inference; Eigen, a template library for linear algebra; googleglog, a library for logging; gflags, a library for commandline flag processing. All these libraries are free software and are provided as tarballs in this package. This software has been tested on Linux, but it should run in other platforms with minor adaptations.

About: TexttoSpeech (TTS) is a kind of speech processing technology that converts text into speech. It involves phonetics, linguistics, digital signal processing technology, computer technology, multimedia technology, and other technologies. It is a frontier technology in Chinese information processing field. With TTS technology, any text used to be read by eyes can also be listened by ears. Changes:Initial Announcement on mloss.org.

About: The code is for computing stateoftheart video descriptors for action recognition. The most uptodate information can be found at: http://lear.inrialpes.fr/people/wang/dense_trajectories Changes:Initial Announcement on mloss.org.

About: A C++ Library for Discrete Graphical Models Changes:Initial Announcement on mloss.org.

About: Fast C++ implementation of the variation of information (Meila 2003) and Rand index (Rand 1971) with MATLAB mex files Changes:Initial Announcement on mloss.org.

About: Link Prediction Made Easy Changes:v1.2.2

About: mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. Changes:New features:
Fix:

About: This is demo program on global thresholding for image of bright small objects, such as aircrafts in airports. the program include four method, otsu,2DTsallis,PSSIM, Smoothnees Method. Changes:Initial Announcement on mloss.org.

About: Software to perform isoline retrieval, retrieve isolines of an atmospheric parameter from a nadirlooking satellite. Changes:Added screenshot, keywords

About: Locally Weighted Projection Regression (LWPR) is a recent algorithm that achieves nonlinear function approximation in high dimensional spaces with redundant and irrelevant input dimensions. At its [...] Changes:Version 1.2.4

About: This is a Matlab/C++ "toolbox" of code for learning and inference with graphical models. It is focused on parameter learning using marginalization in the hightreewidth setting. Changes:Initial Announcement on mloss.org.

About: The KernelMachine Library is a free (released under the LGPL) C++ library to promote the use of and progress of kernel machines. Changes:Updated mloss entry (minor fixes).

About: MetropolisHastings alogrithm is a Markov chain Monte Carlo method for obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult. Thi sequence can be used to approximate the distribution. Changes:Initial Announcement on mloss.org.

About: OpenPRNBEM is an C++ implementation of Naive Bayes Classifier, which is a wellknown generative classification algorithm for the application such as text classification. The Naive Bayes algorithm requires the probabilistic distribution to be discrete. OpenPRNBEM uses the multinomial event model for representation. The maximum likelihood estimate is used for supervised learning, and the expectationmaximization estimate is used for semisupervised and unsupervised learning. Changes:Initial Announcement on mloss.org.

About: This is a class to calculate histogram of LBP (local binary patterns) from an input image, histograms of LBPTOP (local binary patterns on three orthogonal planes) from an image sequence, histogram of the rotation invariant VLBP (volume local binary patterns) or uniform rotation invariant VLBP from an image sequence. Changes:Initial Announcement on mloss.org.

About: This is a implementation of the classic P3P(Perspective 3Points) algorithm problem solution in the Ransac paper "M. A. Fischler, R. C. Bolles. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM, Vol 24, pp 381395, 1981.". The algorithm gives the four probable solutions of the P3P problem in about 0.1ms, and can be used as input of the consequent RANSAC step. The codes needs the numerics library VNL which is a part of the widely used computer vision library VXL. One can download & install it from http://vxl.sourceforge.net/. Changes:Initial Announcement on mloss.org.

About: It's a C++ program for symmetric matrix diagonalization, inversion and principal component anlaysis(PCA). The matrix diagonalization function can also be applied to the computation of singular value decomposition (SVD), Fisher linear discriminant analysis (FLDA) and kernel PCA (KPCA) if forming the symmetric matrix appropriately. Changes:Initial Announcement on mloss.org.

About: This program is a C++ implementation of Linear Discriminant Function Classifier. Discriminant functions such as perceptron criterion, cross entropy (CE) criterion, and least mean square (LMS) criterion (all for multiclass classification problems) are supported in it. The program uses a sparsedata structure to represent the feature vector to seek higher computational speed. Some other techniques such as online updating, weights averaging, gaussian prior regularization are also supported. Changes:Initial Announcement on mloss.org.

About: This program is a C++ implementation of Naive Bayes Classifier, which is a wellknown generative classification algorithm for the application such as text classification. The Naive Bayes algorithm requires the probabilistic distribution to be discrete. The program uses the multinomial event model for representation, the maximum likelihood estimate with a Laplace smoothing technique for learning parameters. A sparsedata structure is defined to represent the feature vector in the program to seek higher computational speed. Changes:Initial Announcement on mloss.org.
