arXiv: cs.AI preprintsInternational6 November 2026
ACSAN: All-Convolutional Self-Attention Network Integrating Convolutional Operations with Vision Transformer
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arXiv:2610.35375v2 Announce Type: replace-cross Abstract: In the past few years, Vision Transformer (ViT) has achieved competitive performance in the field of computer vision. However, there still remain some problems. For instance, ViTs rely on large-scale training data since they simply contain a large number of trainable parameters, which slows down their learning efficiency and limits their applicability in resource-constrained scenarios. In this paper, we propose a novel deep learning model, namely All-Convolutional Self-Attention Network (ACSAN), which applies convolution operations to r
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