Although self-attention has advanced remote sensing image superresolution (RSISR), its high computational cost and large-scale variations in remote sensing imagery hinder efficient deployment on edge devices. Given this, we propose a lightweight RSISR network, called the direction-aware residual network (DireNet), whic...
Wei Xue, Meng-Cheng Ma, Ming-Yang Du et al.· IEEE Geoscience and Remote S...· 0 citations
Radar signal sorting is a fundamental task in passive electromagnetic sensing that separates pulses emitted by multiple radars from densely interleaved streams. Existing supervised deep learning methods often require large labeled datasets and iterative optimization, limiting their applicability in non-cooperative, lat...
Long-Kun Kuang, Xuan Chen, Ming-Yang Du et al.· Italian National Conference...· 0 citations
This work proposes a lightweight dual-domain attention aggregation network (LDANet), aiming to achieve image super-resolution with both high efficiency and high quality, and proposes the pixel-embedding channel attention module, which achieves cross-channel global context awareness by jointly modeling pixel-level spati...
Wei Xue, Meng-Cheng Ma, Bing-Wen Hu et al.· ACM Transactions on Multimed...· 0 citations
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