Open Source Algorithms - Page 18

Hasher is a .NET class library to help programmers implement standard hashing and checksum algorithms into their own software. Written entirely in C#, Hasher providers a uniform interface to easily use any of the algorithms contained within this library

An experimental language designed to be very simple, but expressive enough to represent mathematical constructions and have strong introspective capabilities.

A C++ library for clipping polygons.

Clone Digger is a duplicate code detection tool, which supports Python and Java languages. Discovered clones can differ in small subexpressions; comments and whitespaces are ignored. Clone digger is platform-independent and is written in Python language

CoPP is an object-oriented framework for developing algorithms for robot path planning. One of of the design goals is to make it easy to make comparisons between various path planning algorithms.

Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments to solve. Coach collects statistics from the training process and supports advanced visualization techniques for debugging the agent being trained. Coach supports many state-of-the-art reinforcement learning algorithms, which are separated into three main classes - value optimization, policy optimization, and imitation learning. Coach supports a large number of environments which can be solved using reinforcement learning.

CodeVault is a program to help you manage your source code snippets, currently supporting syntax highlighting for 21 languages, has printing capabilities,exporting to RTF and HTML files, favorites, attachments, backup,import and merge libraries&much more

A collection of useful C++ code snippets collected and published by John W. Ratcliff over the course of many years.

Many people love programming contests. There are tons of contests or online judges like TopCoder, UVA, SPOJ, etc. This project's goal is to store and keep track of what a programmer have done and studied so far.

This project contains solutions for all training lessons that can be found on website codility.com: https://codility.com/programmers/lessons/ The solutions are written in programming language C, because I presumed that it is the most basic language anyone can easily understand and the fact that many other languages have a basis in C means the code can be easily rewritten in that language.

Wienert S, Heim D, Kotani M, Lindequist B, Stenzinger A, Ishii M, Hufnagl P, Beil M, Dietel M, Denkert C, Klauschen F. CognitionMaster: an object-based image analysis framework. Diagn Pathol 2013, 8:34

Colibri is a repository for source code developed in ENVI/IDL under the Open Source Initiative. It contains a wide variety of algorithms and applications which are of interest for the remote sensing community. The code is organized in a hierarchical way. At the lowest level, common code performing all kinds of basic functionality is available to the higher levels, i.e. classes and applications. Classes are object based functionalities performing more specific tasks. Both common code and classes are the building blocks for the applications which perform well delineated tasks. All common code, classes and applications are well documented. The complete set of code and documentation are available to the remote sensing community. ENVI/IDL code developers and remote sensing researchers are requested to actively contribute to this ENVI/IDL Code Library in order to obtain a solid reference of user developed applications for the remote sensing community.

A library of data structures with a unified API, written in portable C. Lists (uni- and bidirectional), a vector, a hash, a balanced tree (RB or AVL), a heap and tuples. Memory management, clone support, error handling.

Combean is a Java framework for mathematical structures and optimization algorithms. Through a set of Java interfaces and JavaBeans-based config, Combean glues optimization codes together - leading to more interoperable, adaptable and flexible solutions.

This project comprises documentation and VBA programming code in respect of a combinations algorithm that I have written. The algorithm is in the Excel file named Combinations.xlsm and the documentation that explains how to use interface and execution of the algorithm is in the pdf file called Combinations.pdf You will need to enable macros in Excel in order to run the algorithm.

A Common Lisp library for representing and manipulating graphs. Algorithms implemented: subgraph isomorphism (Ullman), automorphism, canonicalization (Nauty), connected-components/union-find.

A subset of the mostly used modules in Jakarta commons implemented in C#. Modules: TypeUtils (Copy, Verify), MapUtils (Merge, Creation), ToStringBuilder, EqualsToBuilder, TypeIntrospector , ListUtils

It consists of a library of Java classes that gives us support the programming of applications. Boring, repetitive tasks will be included in CommunityUtil. So this is the aim: to provide fast that encapsulates all classes complicated tasks.

Comparador de Algoritmos de Ordenação

CILib is a framework for developing Computational Intelligence software in swarm intelligence, evolutionary computing, neural networks, artificial immune systems, fuzzy logic and robotics.

CoRoPa stands for Computational Rough Paths. The aim of CoRoPa is to provide a software framework for various ideas related to Rough Path Theory, including rough differential equations and the digital description of serial data streams.

Automatic Solver for Railway-related conflicts

Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.

Consistent Depth is a research project developed by Facebook Research that presents an algorithm for reconstructing dense and geometrically consistent depth information for all pixels in a monocular video. The system builds upon traditional structure-from-motion (SfM) techniques to provide geometric constraints while integrating a convolutional neural network trained for single-image depth estimation. During inference, the model fine-tunes itself to align with the geometric constraints of a specific input video, ensuring stable and realistic depth maps even in less-constrained regions. This approach achieves improved geometric consistency and visual stability compared to prior monocular reconstruction methods. The project can process challenging hand-held video footage, including those with moderate dynamic motion, making it practical for real-world usage.