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   Articles with "kernel attention" as a keyword



Recurrent Large Kernel Attention Network for Efficient Single Infrared Image Super-Resolution

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2023.3344830

Abstract: Infrared imaging has broad and important applications. However, the infrared detector manufacture technique limits the detector resolution and the resolution of infrared images. In this work, we design a Recurrent Large Kernel Attention Neural Network… read more here.

Keywords: attention; kernel attention; rlka net; resolution ... See more keywords

Diffusion Kernel Attention Network for Brain Disorder Classification

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recommendations! Published in 2022 at "IEEE Transactions on Medical Imaging"

DOI: 10.1109/tmi.2022.3170701

Abstract: Constructing and analyzing functional brain networks (FBN) has become a promising approach to brain disorder classification. However, the conventional successive construct-and-analyze process would limit the performance due to the lack of interactions and adaptivity among… read more here.

Keywords: brain disorder; kernel attention; brain; attention ... See more keywords

SmartFallNet: A Vision Transformer and GRU‐Based Dynamic Model With Adaptive Kernel Attention for Precision Fall Detection

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recommendations! Published in 2025 at "Computational Intelligence"

DOI: 10.1111/coin.70152

Abstract: Falls among the elderly remain a critical public health concern, often leading to severe injuries or fatalities. In response, we propose SmartFallNet, an advanced deep learning framework designed for accurate and real‐time fall detection in… read more here.

Keywords: detection; kernel attention; smartfallnet; model ... See more keywords

Research on CNC Machine Tool Spindle Fault Diagnosis Method Based on Deep Residual Shrinkage Network with Dynamic Convolution and Selective Kernel Attention Model

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recommendations! Published in 2025 at "Algorithms"

DOI: 10.3390/a18090569

Abstract: Rolling bearing vibration signals are often severely affected by strong external noise, which can obscure fault-related features and hinder accurate diagnosis. To address this challenge, this paper proposes an enhanced Deep Residual Shrinkage Network with… read more here.

Keywords: dynamic convolution; kernel attention; network; selective kernel ... See more keywords