Showing 3 open source projects for "the bp neural network"

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    Securden Privileged Account Manager

    Unified Privileged Access Management

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    Real Time Accounts Payable Automation.

    Invoice capture and automation seamlessly integrated with your accounting software

    Yooz provides the smartest, most powerful, and easiest-to-use cloud-based E-invoicing and Purchase-to-Pay automation solution. It delivers unmatched savings, speed, and security with affordable zero-risk subscriptions to more than 5,000 customers and 300,000 users worldwide.
  • 1
    SuperImage

    SuperImage

    Sharpen your low-resolution pictures with the power of AI upscaling

    Sharpen your low-resolution pictures with the power of AI upscaling. SuperImage is a neural network-based image upscaling build with the MNN deep learning framework and the Real-ESRGAN algorithm. By leveraging the power of your device's GPU, SuperImage is able to upscale and restore the details of your images without uploading them to the internet, keeping your data secure. SuperImage is a neural network-based image upscaling application for Android built with the MNN deep learning framework...
    Downloads: 8 This Week
    Last Update:
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  • 2
    G2SConverter

    G2SConverter

    Convert models from GoldSource engine to Source engine with AI

    Convert models from GoldSource engine to the Source engine with AI. This utility converts GoldSource engine models to Source engine models. A feature of this utility is the ability to improve the quality of textures of models using Upscaling, deblurring, and normal map generating. All operations to improve the quality of textures are performed by neural networks. To improve the quality of the texture, it is first Upscaled using RealESRGAN. The user can select scaling factor: x2, x4 or x8...
    Downloads: 0 This Week
    Last Update:
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  • 3
    Robust Video Matting (RVM)

    Robust Video Matting (RVM)

    Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX

    ... and matting quality. Furthermore, we propose a novel training strategy that enforces our network on both matting and segmentation objectives. This significantly improves our model's robustness. Our method does not require any auxiliary inputs such as a trimap or a pre-captured background image, so it can be widely applied to existing human matting applications. RVM is specifically designed for robust human video matting.
    Downloads: 1 This Week
    Last Update:
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