Search Results for "c programming framework"

SAGA - System for Automated Geoscientific Analyses - is a Geographic Information System (GIS) software with immense capabilities for geodata processing and analysis. SAGA is programmed in the object oriented C++ language and supports the implementation of new functions with a very effective Application Programming Interface (API). Functions are organised as modules in framework independent Module Libraries and can be accessed via SAGA’s Graphical User Interface (GUI) or various scripting environments (shell scripts, Python, R, ...). Please provide the following reference in your work if you are using SAGA: Conrad, O., Bechtel, B., Bock, M., Dietrich, H., Fischer, E., Gerlitz, L., Wehberg, J., Wichmann, V., and Boehner, J. (2015): System for Automated Geoscientific Analyses (SAGA) v. 2.1.4. ...

LaMa is a C++11 software library for robotic localization and mapping developed at the Intelligent Robotics and Systems (IRIS) Laboratory at the University of Aveiro - Portugal. It includes a framework for 3D volumetric grids (for mapping), a localization algorithm based on scan matching, and two SLAM solutions (an Online SLAM and a Particle Filter SLAM).

MicroCity is a framework for spatial analysis and simulation. It is lightweight, fast, portable, extendable and user friendly. Users can easily operate large GIS and Grid data and perform Spatial, Fractal, Network analysis and simulation.

FastEasyMapping is a lightweight and high-performance framework designed for mapping JSON or other data formats into native Objective-C objects on iOS. It simplifies the process of converting raw data into models and is built with a focus on speed and efficiency, making it suitable for apps dealing with large datasets or frequent network responses.

...RTKLIB consists of a portable program library and several APs (application programs) utilizing the library. This port includes only a library (.so or .dll) for the C/C++ language and a .dll for C#/.NET Framework. RTKSharp is compatible with Windows and Linux using the .NET/Mono Assembly withoout the need of recompilation/cross-building.

...Targeted algorithms for high resolution optical images (SPOT, Quickbird, Worldview, Landsat, Ikonos), hyperspectral sensors (Hyperion) or SAR (TerraSarX, ERS, Palsar) are available. Orfeo ToolBox has three main access depending on the category of user: write processing chains in C++ using existing filters or creating new ones, use the OTB applications, which is a plugin-based framework allowing to extend high-level processing chains from various environment ( command-line, QT, QGis, Python....) or use Monteverdi, a software for everyday life image manipulation and analysis.

UPDATE March 14, 2018 Repository and tracking officially moved to github. https://github.com/opticks-org/opticks Sourceforge mailing lists are still in use. Opticks is an open source remote sensing application and development framework.

Astral Projection is a testing tool for iOS applications that use the CoreLocation framework. AP allows for testing location-aware apps on both the device and the simulator, using configurable location data sources like a GPX file or a remote agent.

OpenDMTP is a protocol/framework that allows communications with small devices (mobile phones, PDA's, and other high-latency/low-bandwidth devices), especially geared towards the transmission of GPS, temperature, and other remote monitoring information.

National University Community Research Institute's NU KEEPERRHHATT Algorithmic Framework is a series of meta-algorithms based upon the Longest Hamiltonian Path Problem for finding high level explanations to social, economic and political behaviour.

RegMAS (Regional Multi Agent Simulator) is a spatially explicit multi-agent model framework, developed in C++ language and designed for long-term simulations of effects of government policies over agricultural systems (farm sizes, incomes, land use..).

pRPL is a general-purpose parallel Raster Processing C++ programming Library. It enables the implementation of parallel raster-based algorithms without requiring a deep understanding of parallel computing, and greatly reduces the development complexity.