Search Results for "data capture framework" - Page 17

This project provides a java implementation of the Captcha project ( see http://www.captcha.net ). A CAPTCHA is a program that can generate and grade tests that: -Most humans can pass. -Current computer programs can't pass.

POGG (Programação Orientada a Gráficos de Gantt) é um modelo de programação que permite a distribuição de tarefas num Sistema Multiagente (SMA) criado com a plataforma JADE (Java Agent DEvelopment Framework), formando uma grade computacional.

Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.

The Vision Analysis Toolkit provides a framework for the development of computer vision algorithms using arbitrary named channel containers, flexible data types, and 1/2/3-D buffers.

JUNG provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. New version now available on GitHub: https://github.com/jrtom/jung/releases/tag/jung-2.1

Highly reusable and extensible Decision-Tree (Max-Gain) framework comprising of comprehensive input-processing and display functionality. Handles nominal, linear, continuous data. For preliminary description, refer - http://sushain.com/blog/archives/

Facilitates data mining/natural language processing experiments to be executed on weblogs, such as classification, clustering and rating. As part of these experiments, it is possible to apply Latent Semantic Analysis.

MIARN(Modules for Intelligent Autonomous Robot Navigation) is a project of robotics perception and interaction. We provide a gui for controlling and visualizing playerstage.sf.net sensors and opencv algorithms

Agent Academy is a Java integrated development framework for creating Intelligent Agents and Multi Agent Systems. Agent Academy seamlessly integrates JADE and WEKA platforms and enables the creation of software agents that use Data Mining models.

A framework for building, deploying and managing well-described REST-ful Web services, including REST-ful Web Services realizations for RSS, XML Topic Maps, Structured Arguments, and Workflow.

Its a model fitting framework which optimizes the model parameters to make the model output match the desired data.

A feedback-enhanced framework for routing in wireless sensor networks. Speeds up the process of implementing routing techniques. Enables piggybacking of routing information on data packets. Written for the Omnet++ simulator and the Mobility Framework.

MMI - Tethys is a framework to facilitate interoperability among environmental systems. It facilitates creation of metadata, data and Web Services following standards. It is currently based on JAVA, AXIS and ANT.

The DataTime Process Framework is intended to support the processing of time-based data in a modular, concurrent, distributed and extensible manner. C++, using YARP, ACE, Qt and MUSCLE on Linux, OSX, Windows and Solaris.

AGISim is a framework for the creation of virtual worlds for artificial intelligence research, allowing AI and human controlled agents to interact in realtime within sensory-rich contexts. AGISim is built on the Crystal Space 3D game engine.

SoFi (Solution Finder) is an extensible Java framework that facilitates rapid development of instructional applications to demonstrate common search and problem solving methods in the field of Artificial Intelligence.

Fungus is a framework for distributed simulation by multi-agents. It uses a very modular architecture. A GUI is provided. In our model, everything is Agent. Even the environnement. You have an access to the communication's 'canals'.

pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g.

Reputation Sentinel OS v3.0: Autonomous Brand Defense Infrastructure Sentinel OS v3.0 is a sovereign AI framework for brand protection and automated response. Built on n8n with a massive 1,500+ logic nodes architecture, it offers depth and privacy far beyond traditional SaaS. Total Data Sovereignty: Unlike expensive monthly platforms, Sentinel OS runs on your own infrastructure. You own your data and your brand's defense. Key Capabilities: Omni-Channel: 24/7 autonomous tracking across X, YouTube, and Telegram. ...

Savant is an open-source, high-level framework for building real-time, streaming, highly efficient multimedia AI applications on the Nvidia stack. It helps to develop dynamic, fault-tolerant inference pipelines that utilize the best Nvidia approaches for data center and edge accelerators. Savant is built on DeepStream and provides a high-level abstraction layer for building inference pipelines.

...It introduces DeepSeek Sparse Attention (DSA), a new attention mechanism that dramatically reduces computational overhead while maintaining strong long-context performance. Built with a scalable reinforcement learning framework, it reaches near-GPT-5 levels of reasoning and outperforms comparable models like DeepSeek-V3.1 and Gemini-3.0-Pro in advanced benchmarks. The model was notably used in competitive AI challenges such as the 2025 International Mathematical Olympiad (IMO) and IOI, achieving top-tier results. DeepSeek-V3.2 also features a large-scale agentic task synthesis pipeline, which generates training data to enhance tool-use intelligence and multi-step reasoning. ...

...It achieves an impressive 80.1% top-1 accuracy on ImageNet-1k without any fine-tuning, showcasing its robustness in open-domain settings. Its training dataset is uncurated and web-sourced, meaning it reflects the biases and risks of large-scale internet data. The model is intended for research use and is not recommended for real-world deployment without domain-specific testing and safety evaluations.