Shypd.aiThe largest open index of AI toolsresidual-attention-network is an open-source research tool that implements a convolutional neural network with an attention mechanism for image classification. It incorporates state-of-the-art feed-forward network architectures.
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residual-attention-network is an open-source implementation of a convolutional neural network that utilizes an attention mechanism for image classification tasks. This network can be integrated with existing state-of-the-art feed-forward network architectures, offering a flexible approach to enhancing image classification performance. The project provides prototxts for the network, as described in the CVPR-2017 Spotlight paper "Residual Attention Network for Image Classification." Researchers can use this repository to experiment with and apply attention mechanisms in their image classification studies, with trained models expected to be released. It supports various configurations, including Attention-56, Attention-92, AttentionNeXt-56, and AttentionNeXt-92, demonstrating competitive performance on datasets like ImageNet.
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