Version 17.46 of dlib C++ Library
Release Notes: This release has focused mostly on minor usability and feature improvements. Some highlights are better support for learning to do sequence labeleing from unbalanced data, new image processing routines, and new tools tools for performing Kalman filtering and recursive least squares filtering.
Other releases
Release Notes: In addition to some bugfixes, this release also brings the following notable improvements to the library: a more accurate SURF feature extractor, a faster cutting plane solver, a routine for computing the singular value decomposition of very large matrices, a tool for performing canonical correlation analysis on large datasets, and simple tools for writing parallel for loops.
Release Notes: This release includes a large number of new minor features and usability improvements. It also includes a new machine learning tool for learning to rank objects. This is the dlib::svm_rank_trainer, an implementation of the well known SVM-Rank algorithm. Moreover, the implementation runs in O(n*log(n)) time and is therefore suitable for use with large training datasets.
Release Notes: This release brings a number of new features to the library. Highlights include a probabilistic CKY parser, tools for creating applications using the Bulk Synchronous Parallel computing model, and two new clustering algorithms: Chinese Whispers and Newman's modularity clustering.
Release Notes: In addition to a number of minor usability and feature improvements, this release also gives dlib's object detection tools the ability to model objects with movable parts.
Release Notes: This release has focused on adding a set of graph cut algorithms. In particular, tools for finding the minimum weight cut on a graph, finding the MAP assignment of a Potts style Markov random field, and structural SVM tools for learning the parameters of such a Markov model have been added.
