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OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations.

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!...

BoostMultiDex is a specialized Android-library created by ByteDance to address a long-standing performance and user-experience problem on older Android devices (specifically Android 4.x and below, i.e. SDK < 21), where loading multiple dex files after installation or upgrade can lead to extremely long “black-screen” freeze times during first startup. Instead of relying on the standard Android MultiDex mechanism, BoostMultiDex reworks the loading strategy by tapping into hidden Dalvik VM...

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...

A mobile application to create accelerometer based activity recognition models directly on the phone. The configuration of the segmentation and feature extraction process chain requires expert knownledge. The prototype was developed in 2012 in a bachelor thesis at the University of Kassel and was optimized and enhanced for an experiment in 2015.

RuleRule is a game which might be of interest to students and researchers of AI, machine learning and related areas. In this game, rules act and modify other rules (including themselves). The goal is to reach a desired condition (e.g. a checkerboard of red and yellow). Versions For a first test of the game mechanics in your browser, download the Javascript version, coded by Jan-Hendrik Vienup (December 2014, GPL) tested with Firefox, MSIE, Chrome, and Safari :...