Showing 5 open source projects for "email/android"

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  • 1
    NanoDet-Plus

    NanoDet-Plus

    Lightweight anchor-free object detection model

    ...These improvements boost previous NanoDet's detection accuracy by 7 mAP on COCO dataset. NanoDet provide multi-backend C++ demo including ncnn, OpenVINO and MNN. There is also an Android demo based on ncnn library. Supports various backends including ncnn, MNN and OpenVINO. Also provide Android demo based on ncnn inference framework.
    Downloads: 15 This Week
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  • 2
    TNN

    TNN

    Uniform deep learning inference framework for mobile

    TNN, a high-performance, lightweight neural network inference framework open sourced by Tencent Youtu Lab. It also has many outstanding advantages such as cross-platform, high performance, model compression, and code tailoring. The TNN framework further strengthens the support and performance optimization of mobile devices on the basis of the original Rapidnet and ncnn frameworks. At the same time, it refers to the high performance and good scalability characteristics of the industry's...
    Downloads: 0 This Week
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  • 3
    Simd

    Simd

    High performance image processing library in C++

    ...The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. The library supports dynamic and static linking, 32-bit and 64-bit Windows, Android and Linux, MSVS, G++ and Clang compilers, MSVS project and CMake build systems.
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    Downloads: 17 This Week
    Last Update:
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  • 4

    ObjectDetector

    Car Detection,Face Detectiom,Object Detection

    Machine learning: This project is used for training new object like Car,Motor Cycle and so on and we use this model(xml file) for detecting in images.In this project we use viola jones algorithm.
    Downloads: 0 This Week
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  • 5

    LiveVideo

    Real-time Video Analysis Software

    ...It applies probabilistic spatiotemporal macroblock filtering (PSMF) and partial decoding processes to effectively detect and track multiple objects with fast computation in H.264|AVC bitstreams with stationary background. The codes were written in Visual C++. For more details, please visit https://www.wonsangyou.com/research/aivision. If you need technical help, please send an email to wyou(at)kaist.ac.kr. When you use this software for your publications, please cite as follows. 1. Wonsang You, M.S. Houari Sabirin, and Munchurl Kim, "Moving object tracking in H.264/AVC bitstream," Lecture Notes in Computer Science, vol. 4577, 2007, pp. 483-492. 2. Wonsang You, M.S. Houari Sabirin, and Munchurl Kim, "Real-time detection and tracking of multiple objects with partial decoding in H.264/AVC bitstream domain," Proceedings of SPIE, vol. 7244, 72440D (February 2009).
    Downloads: 0 This Week
    Last Update:
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