Search Results for "mind-mapping"
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Showing 7 open source projects for "mind-mapping"
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Auth0 B2B Essentials: SSO, MFA, and RBAC Built InAuth0's B2B Essentials plan gives you everything you need to ship secure multi-tenant apps. Unlimited orgs, enterprise SSO, RBAC, audit log streaming, and higher auth and API limits included. Add on M2M tokens, enterprise MFA, or additional SSO connections as you scale.
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CRUSH
Data reduction and imaging for select astronomical cameras
CRUSH is a pioneering reduction and imaging suite for many astronomical cameras operating at far-infrared, submillimeter and millimeter wavelengths, such as SHARC-2, SCUBA-2, LABOCA, GISMO, or SOFIA/HAWC+ (to name a few). -
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The JTS Topology Suite is an API for modelling and manipulating 2-dimensional linear geometry. It provides numerous geometric predicates and functions. JTS conforms to the Simple Features Specification for SQL published by the Open GIS Consortium.
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FunctionalJ is a library which makes it easy to use functional programming patterns in Java, such as representing functions as objects, partial function application, higher-order functions, mapping, folding, and more.
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An attempt to design minimum cost broadband networks with the use of a modified version of the Particle Swarm Optimization method. A GIS subsystem is used for the visualization of data and results.
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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The K.U.Leuven JCHR System is an integration of Constraint Handling Rules (CHR) and Java designed with three aims in mind: user-friendliness, flexibility and efficiency. http://www.cs.kuleuven.be/~petervw/JCHR/
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Centre is a synthetic trajectory generator environment that aim to generate semantic-based trajectory datasets usable for spatio-temporal data-mining algorithms in testing and validation process.
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MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.
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