Showing 7 open source projects for "energy"

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  • 1
    ESP32 iPhone Agent

    ESP32 iPhone Agent

    Let an AI model use a real iPhone with a $7 ESP32

    ...Compatible vision models interpret screenshots and generate actions such as taps, swipes, typing, and navigation. The microcontroller executes these actions through USB mouse and keyboard interfaces using iOS AssistiveTouch. Bluetooth Low Energy connects the application with the hardware controller. The system operates without jailbreaking, a Mac, or an Apple developer account. It supports OpenAI-compatible vision models for automated mobile workflows.
    Downloads: 0 This Week
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  • 2
    Cactus

    Cactus

    Low-latency AI inference engine optimized for mobile devices

    Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing large models to run within the constraints of mobile hardware. ...
    Downloads: 0 This Week
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  • 3
    Uranie

    Uranie

    Uranie is CEA's uncertainty analysis platform, based on ROOT

    Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is available both for Unix and Windows platforms (a dedicated platform archive is available on request). ...
    Downloads: 5 This Week
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  • 4

    bnns

    Research tool for interactive training of artificial neural networks.

    BNNS is a research tool for interactive training of artificial neural networks based on the Response Function Plots visualization method. It enables users to simulate, visualize and interact in the learning process of a Multi-Layer Perceptron on tasks which have a 2D character. Tasks like the famous two-spirals task or classification of satellite image data.
    Downloads: 0 This Week
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  • 5

    LBP in multiple platforms

    LBP implementation in multiple computing platforms (ARM,GPU, DSP...)

    The Local Binary Pattern (LBP) is a texture operator that is used in several different computer vision applications and implemented in a variety of platforms. When selecting a suitable LBP implementation platform, the specific application and its requirements in terms of performance, size, energy efficiency, cost and developing time has to be carefully considered. This is a software toolbox that collects software implementations of the Local Binary Pattern operator in several platforms: - OpenCL for CPU & GPU - OpenCL for GPU (branchless) - C code optimized for ARM - OpenGL ES 2.0 shaders mobile GPUs - C code for TI C64x DSP core (branchless) - C code for TTA processor synthesis If you use the code somewhere, please cite: Bordallo López M., Nieto A., Boutellier J., Hannuksela J., and Silvén O. ...
    Downloads: 0 This Week
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  • 6

    Urban Challege

    Hardware and software for self-driving vehicles

    The DARPA Urban Challenge race for robot vehicles took place on Nov 3, 2007. We pose a new urban challenge: build a safe, convenient, energy efficient people mover. This site provides the hardware and software for a prototype system.
    Downloads: 0 This Week
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  • 7
    Surviving bots is continuous software application in Java that will guide robots to search for energy source around it, tap it and explore ahead for survival and thus evolve into much more advance system.Software is ment to be hardware independent.
    Downloads: 0 This Week
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