Aggregated Residual Transformations for Deep Neural Networks

E1153672 UNEXPLORED

"Aggregated Residual Transformations for Deep Neural Networks" is the research paper that introduced the ResNeXt architecture, a deep convolutional neural network design that improves accuracy and efficiency by using grouped convolutions and aggregated residual transformations.

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ResNeXt introducedInPaper Aggregated Residual Transformations for Deep Neural Networks