dlib is a C++ library for developing portable applications dealing with networking, threads, graphical interfaces, data structures, linear algebra, machine learning, XML and text parsing, numerical optimization, Bayesian nets, and numerous other tasks.
|Tags||Scientific/Engineering Artificial Intelligence Software Development Libraries Internet Web HTTP Servers|
|Operating Systems||Windows Windows Windows OS Independent Windows Mac OS X POSIX|
Release Notes: This release has primarily focused on improving the flexibility and ease of use of the object detection tools.
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.