Showing 4 open source projects for "process"

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  • 1
    nndeploy

    nndeploy

    An Easy-to-Use and High-Performance AI Deployment Framework

    ...The framework focuses on making it easier to transform trained AI models into production-ready applications that can run efficiently on desktops, mobile devices, servers, and edge computing hardware. Developers can use visual workflows to design and configure AI processing pipelines by connecting modular nodes that represent different stages of the inference process. The system supports multiple inference engines and hardware accelerators, allowing the same AI workflow to run on different platforms without significant modifications. nndeploy also includes performance optimization techniques such as parallel execution, memory reuse, and hardware-accelerated operations to improve inference speed.
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  • 2
    AabResGuard

    AabResGuard

    The tool of obfuscated aab resources

    AabResGuard is a resource-obfuscation and resource-packing tool developed by ByteDance for Android applications. Its primary purpose is to protect and shrink the resource assets inside Android App Bundles (AAB), making reverse engineering and tampering harder while reducing final package size. It can be integrated as a command-line tool or a Gradle plugin, so developers can adopt it with minimal disruption to their existing Android build pipelines. Historically, it was used internally by...
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  • 3
    BoostMultiDex

    BoostMultiDex

    Load multiple dex files on low Android version devices

    ...It adopts a multi-stage loading approach (DEX bytecode → DEX file → ODEX file) to pick the fastest viable route at runtime, and optionally performs optimization (OPT) in a separate process with interruption/recovery support — minimizing startup time and preserving stability.
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  • 4
    android-activity-miner

    android-activity-miner

    Activity-Miner for Android

    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.
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