Search Results for "algorithms"
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Showing 9 open source projects for "algorithms"
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MNN
MNN is a blazing fast, lightweight deep learning framework
MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models, and has industry leading performance for inference and training on-device. At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity... -
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OpenCV
Open Source Computer Vision Library
The Open Source Computer Vision Library has >2500 algorithms, extensive documentation and sample code for real-time computer vision. It works on Windows, Linux, Mac OS X, Android, iOS in your browser through JavaScript. Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials! -
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Poker Bot AI
Artificial Intelligence Poker Bot for popular apps on Android
...You can receive live hints from the AI (like RTA‑style advice) or choose automated play under your defined constraints. What makes our poker AI different? - Trained on over 1 billion poker hands collected since 2016, enabling strong neural decision models. - Behavior algorithms that mimic human playing patterns, helping the bot blend into realistic gameplay environments. - Integrated use of opponent statistics (VPIP, AF, 3‑Bet, C‑Bet, PFR, etc.) to optimize strategy and adapt to pool tendencies. - Regular software updates and lifetime support ensure stability. Github: https://github.com/PokerBotAI -
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Simd
High performance image processing library in C++
The Simd Library is a free open source image processing library, designed for C and C++ programmers. It provides many useful high performance algorithms for image processing such as: pixel format conversion, image scaling and filtration, extraction of statistic information from images, motion detection, object detection (HAAR and LBP classifier cascades) and classification, neural network. The algorithms are optimized with using of different SIMD CPU extensions. In particular the library supports following CPU extensions: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2 and AVX-512 for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM. ... -
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DGRLVQ
Dynamic Generalized Relevance Learning Vector Quantization
Some of the usual problems for Learning vector quantization (LVQ) based methods are that one cannot optimally guess about the number of prototypes required for initialization for multimodal data structures i.e.these algorithms are very sensitive to initialization of prototypes and one has to pre define the optimal number of prototypes before running the algorithm. If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different categories in between, then the other points act as a barrier and the prototype will not find its optimum position during training. ... -
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nunn
This is an implementation of a machine learning library in C++17
nunn is a collection of ML algorithms and related examples written in modern C++17. -
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neural network designer
a dbms for neural nets. Chatbots, DTrees, random forests, n-grams,...
...It is probably best compared to a database management system, but for neural networks instead of relational data. As such, the library is optimized for handling any type of data-size by using advanced streaming and caching algorithms. With the designer, you are able to create different types of decision trees, random forests, n-grams, pattern-matchers, conversational agents and all sorts of AI related algorithms. You can combine statistical approaches as well as pattern matchers or others. Do natural language processing, image or data analysis & interpretation,... -
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...The main idea behind this tool, is to provide case-special techniques rather than general solutions to resolve complicated mathematical calculations. This will lead to have more efficient defuzzification algorithms for Mamdani's model. Most systems in Mamdani's model can be defuzzified in O(n²) or even O(n) time which n is number of membership functions in output.
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OpenSkyNet - Moving towards a comprehensive artificial intelligence solution for game developers under the LGPL. The goals are to implement action selection solvers, robust steering behaviors (including pathfinding algorithms), and machine learning.
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