KCLA is a linear-complexity layer attention mechanism that exploits high key cosine similarity to preserve dynamic updates and long-range cross-layer connections.
Devel- opment of skip connection in deep neural networks for computer vision and medical image analysis: A survey,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
IncepDeHazeGAN is a GAN with Inception blocks and multi-layer feature fusion that claims state-of-the-art single-image dehazing performance on satellite datasets.
citing papers explorer
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Enhancing Layer Interaction Using Key-Correlated Layer Attention
KCLA is a linear-complexity layer attention mechanism that exploits high key cosine similarity to preserve dynamic updates and long-range cross-layer connections.
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IncepDeHazeGAN: Novel Satellite Image Dehazing
IncepDeHazeGAN is a GAN with Inception blocks and multi-layer feature fusion that claims state-of-the-art single-image dehazing performance on satellite datasets.