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Convolutional Triplet Attention Module by dfliusgd is a document available to read on EtoBox.

What is Convolutional Triplet Attention Module about?

The document presents a novel attention mechanism called triplet attention, which efficiently captures cross-dimensional interactions in input tensors using a three-branch structure. This method enhances feature representations with minimal computational overhead and can be integrated into existing convolutional neural networks. The effectiveness of triplet attention is demonstrated through various computer vision tasks, including image classification and object detection, with empirical results supporting

Author

dfliusgd

Language

EN