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Super-Resolution of Remote Sensing Images via the Parallel Lattice Attention Network

Deep learning-based super-resolution models often struggle to balance capturing long-range dependencies with computational efficiency, as convolutional neural networks focus on local features while transformers incur high computational costs. To address this tradeoff, we propose a parallel lattice a...

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Principais autores: Allen Patnaik, Arpit Gour, M. K. Bhuyan, Karl F. MacDorman, Sultan Alfarhood, Mejdl Safran
Format: Artigo
Jezik:Inglês
Izdano: IEEE 2026-01-01
Serija:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Online dostop:https://ieeexplore.ieee.org/document/11370168/
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