Showing 2 open source projects for "linux image"

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    ResNeXt

    ResNeXt

    Implementation of a classification framework

    ResNeXt is a deep neural network architecture for image classification built on the idea of aggregated residual transformations. Instead of simply increasing depth or width, ResNeXt introduces a new dimension called cardinality, which refers to the number of parallel transformation paths (i.e. the number of “branches”) that are aggregated together. Each branch is a small transformation (e.g. bottleneck block) and their outputs are summed—this enables richer representation without excessive...
    Downloads: 0 This Week
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  • 2
    fast-neural-style

    fast-neural-style

    Feedforward style transfer

    The fast-neural-style project is an implementation of neural style transfer techniques optimized for real-time image processing. It uses convolutional neural networks to apply artistic styles to images, enabling users to transform photos into stylized outputs inspired by famous artworks. Unlike earlier approaches that required expensive optimization per image, this project leverages feed-forward networks to achieve fast inference, making style transfer practical for real-world applications....
    Downloads: 0 This Week
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