Search Results for "c programming framework" - Page 3
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216 projects for "c programming framework" with 2 filters applied:
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Lush is a Lisp dialect with extensions for object-oriented and array-oriented programming. Lush is intended for prototyping numerically intensive applications and is designed for easy integration of existing C/C++/Fortran codes.
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GNU Prolog
The GNU Prolog native compiler
GNU Prolog is a free implementation (under GPL) of the logic programming language PROLOG. It can compile to native machine code which is extremely fast in execution. Another feature is the included constraint solver. -
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SMILI
Scientific Visualisation Made Easy
The Simple Medical Imaging Library Interface (SMILI), pronounced 'smilie', is an open-source, light-weight and easy-to-use medical imaging viewer and library for all major operating systems. The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with... -
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Logic Programming and Deductive Database system (Tabled Prolog) for Unix, Mac, and Windows.
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EcoLab is a C++ based Agent Based Modelling system, with emphasis on high performance computing for scaling to large simulations.
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ToRA
Tool-integrated Reasoning LLM Agents
ToRA is an open-source framework developed by Microsoft for building tool-integrated reasoning agents powered by large language models. The project focuses on improving the ability of AI systems to solve complex mathematical and analytical problems by combining natural language reasoning with external computational tools. Instead of relying solely on text generation, the system dynamically invokes tools such as symbolic solvers or programming libraries when deeper computation is required. ... -
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The Algorithms - C #
Collection of various algorithms in mathematics, machine learning
TheAlgorithms/C is an open-source repository that provides implementations of classic algorithms and data structures written in the C programming language. The project is part of the larger “The Algorithms” initiative, which aims to create educational resources by implementing algorithms in multiple programming languages. Within the C repository, contributors implement algorithms from many areas of computer science including sorting, searching, graph processing, mathematics, machine learning, and numerical methods. ... -
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SNOBOL4, while known primarily as a string language excels at any task involving symbolic manipulations. It provides run time typing, garbage collection, user data types, on the fly compilation.
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Detectron
FAIR's research platform for object detection research
Detectron is an object detection and instance segmentation research framework that popularized many modern detection models in a single, reproducible codebase. Built on Caffe2 with custom CUDA/C++ operators, it provided reference implementations for models like Faster R-CNN, Mask R-CNN, RetinaNet, and Feature Pyramid Networks. The framework emphasized a clean configuration system, strong baselines, and a “model zoo” so researchers could compare results under consistent settings. ... -
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SIG Rust
Rust language bindings for TensorFlow
SIG Rust provides idiomatic Rust bindings for TensorFlow, making it possible for developers to work with TensorFlow functionality from within the Rust programming language. Rather than replacing TensorFlow itself, it acts as an integration layer that connects Rust applications to the TensorFlow C API. The repository is designed for developers who want Rust’s performance, safety, and systems programming strengths while still accessing TensorFlow’s machine learning capabilities. It includes setup instructions that explain how the crate can automatically download or compile the required TensorFlow shared libraries, which lowers the barrier to getting started. ... -
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Mars Framework
Mars is a tensor-based unified framework for large-scale data
Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments. -
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FasterTransformer
Transformer related optimization, including BERT, GPT
FasterTransformer is a high-performance inference library designed to accelerate transformer-based models such as BERT, GPT, and T5 on NVIDIA GPUs. It provides optimized implementations of transformer encoder and decoder layers using CUDA, cuBLAS, and custom kernels to maximize throughput and minimize latency. The library supports multiple deep learning frameworks, including TensorFlow, PyTorch, and Triton, allowing developers to integrate it into existing pipelines without major changes. It... -
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Guia do Cientista de Dados das Galáxias
Repository for gathering information on study materials
...The repository collects links to books, podcasts, tutorials, datasets, communities, and study groups that can help learners navigate the field of data science more efficiently. Instead of focusing on a single software framework, the project functions as a curated knowledge hub where contributors organize resources into thematic categories such as visualization, machine learning, programming languages, and analytics methodologies. This approach makes it easier for beginners and professionals to discover relevant tools, learning materials, and professional communities. -
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Effective TensorFlow 2
TensorFlow tutorials and best practices
Effective Tensorflow is an open-source repository that provides tutorials and best practices for developing machine learning models using the TensorFlow framework. The project focuses on helping developers write efficient, maintainable, and reliable TensorFlow code when building deep learning systems. It includes practical guidelines that explain common pitfalls in neural network training, such as numerical instability and gradient-related issues. The repository also demonstrates techniques... -
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LTI-Lib is an object oriented computer vision library written in C++ for Windows/MS-VC++ and Linux/gcc. It provides lots of functionality to solve mathematical problems, many image processing algorithms, some classification tools and much more...
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Agentopia
Java5 mobile agents in peer2peer containers without stubs/skeletons.
Agentopia is a programming framework (API) for Java 5 mobile agents in peer-to-peer networks. Main features: Routing around firewalls, anonymity, and it is extremely easy to write new agents. No RMI, no CORBA, just plain Java bytecode loading. -
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uTensor
TinyML AI inference library
uTensor is an embedded machine learning inference framework designed to run neural network models on resource-constrained devices such as microcontrollers and Internet-of-Things hardware. The project focuses on enabling TinyML deployments by translating trained machine learning models into efficient C++ code that can execute directly on embedded systems. Instead of training models on-device, the framework uses an offline workflow that converts trained TensorFlow graphs into optimized inference kernels suitable for constrained environments. ... -
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The Mobility Open Architecture Simulation and Tools (MOAST) framework aids in the development of autonomous robots. It includes an architecture, control modules, interface specs, and data sets and is fully integrated with the USARSim simulation system.
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Virtual Laboratory Environment
A multi-modeling and simulation environment to study complex systems
...The VLE environment provides an IDE to develop C++ models, DEVS coupled models. VLE have also three ports to use the VFL with Python, Java and R programming languages. -
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When to use TensorFlowSharp
TensorFlow API for .NET languages
When to use TensorFlowSharp is a .NET binding for the TensorFlow machine learning framework that allows developers to run TensorFlow models directly from C# and other .NET languages. The project exposes TensorFlow’s native C API through a strongly typed interface designed to integrate naturally with the .NET ecosystem. Its primary purpose is to enable developers working in Microsoft-based environments to load trained TensorFlow models and perform inference or additional training within .NET applications. ... -
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P3: The Portable Unix Programming System
Multi-process homeostatic software agent library
PUPS/P3 facilitates development of multi-process multi-host computations by providing tools to emulate colonies of homeostatic organisms. It permits persistent computation, homeostatic resource protection, and asychronous interprocess communication. -
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FARSA
Framework for Autonomous Robotics Simulation and Analysis
FARSA is a collection of integrated open-source object-oriented C++ libraries that allow to experiment with autonomous robots. It allow to simulate different robotic platforms (the iCub humanoid and the khepera, e-puck, and marxbot wheeled robots), design the sensory-motor system of the robot/s, design the environment in which the robot/s operate, design the robot neural controller, and adapt the free parameters of the robot. -
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Logic Lab
This is a suite of mathematical software solvers GUI
This is a suite of mathematical software solvers interface on DLV and other command-line solvers. It helps researchers and students to better comprehend their declarative definitions published on papers. The user can have links to the related papers and to the software of the corresponding definitions. -
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Scilab Image Processing Toolbox
Advanced image processing toolbox for Scilab on Unix/Linux/Mac OS
SIP is the image processing and computer vision package for SciLab, a free Matlab-like programming environment. SIP reads/writes images in formats like JPEG, PNG, and BMP. It does filtering, segmentation, edge detection, morphology, and shape analysis. Download from Git http://siptoolbox.sourceforge.net/devel -
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LightPCC
Parallel pairwise correlation computation on Intel Xeon Phi clusters
The first parallel and distributed library for pairwise correlation/dependence computation on Intel Xeon Phi clusters. This library is written in C++ template classes and achieves high speed by exploring the SIMD-instruction-level and thread-level parallelism within Xeon Phis as well as accelerator-level parallelism among multiple Xeon Phis. To facilitate balanced workload distribution, we have proposed a general framework for symmetric all-pairs computation by building provable bijective functions between job identifier and coordinate space for the first time.
