Visual Attention Networks (VANs) leveraging Large Kernel Attention (LKA) have demonstrated remarkable performance in diverse computer vision tasks, often outperforming Vision Transformers (ViTs) in ...

Abstract: Graph convolutional networks (GCNs) have emerged as a prominent research focus for hyperspectral image classification (HSIC). However, existing GCN-based HSIC methods still face the ...

Normalization layers have become fundamental components of modern neural networks, significantly improving optimization by stabilizing gradient flow, reducing sensitivity to weight initialization, and ...

Event-based cameras are bio-inspired vision sensors that mimic the sparse and asynchronous activation of the animal retina, offering advantages such as low latency and low computational load in ...

U-Net and its variants have been widely used in the field of image segmentation. In this paper, a lightweight multi-scale Ghost U-Net (MSGU-Net) network architecture is proposed. This can efficiently ...

Abstract: In very large scale integration (VLSI) circuit physical design, precise congestion prediction during placement is crucial for enhancing routability and accelerating design processes.

No matter the season, it’s always a good idea to bring an extra jacket along when you’re heading outside. But as temps start to drop, dressing wisely is even more important (and we’re not just talking ...