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   Articles with "block attention" as a keyword



A depthwise separable dense convolutional network with convolution block attention module for COVID-19 diagnosis on CT scans

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recommendations! Published in 2021 at "Computers in Biology and Medicine"

DOI: 10.1016/j.compbiomed.2021.104837

Abstract: Coronavirus disease 2019 (COVID-19) has caused more than 3 million deaths and infected more than 170 million individuals all over the world. Rapid identification of patients with COVID-19 is the key to control transmission and… read more here.

Keywords: depthwise separable; attention module; network; block attention ... See more keywords

Block Attention and Switchable Normalization Based Deep Learning Framework for Segmentation of Retinal Vessels

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recommendations! Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2023.3265729

Abstract: The presence of high blood sugar levels damages blood vessels and causes an eye condition called diabetic retinopathy. The ophthalmologist can detect this disease by looking at the variations in retinal blood vasculature. Manual segmentation… read more here.

Keywords: retinal vessels; segmentation; block attention; model ... See more keywords

Multi-Block Attention for Efficient Channel Estimation in IRS-Assisted mmWave MIMO

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recommendations! Published in 2025 at "IEEE Transactions on Communications"

DOI: 10.1109/tcomm.2025.3618696

Abstract: Intelligent Reflecting Surfaces (IRSs) are a promising technology for enhancing the spectral and energy efficiency of millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. In these systems, accurate channel estimation remains challenging due to the passive nature… read more here.

Keywords: block attention; estimation irs; attention; channel estimation ... See more keywords

Identification and Suppression of Multicomponent Noise in Audio Magnetotelluric Data Based on Convolutional Block Attention Module

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recommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2024.3361942

Abstract: Audio magnetotelluric (AMT) is commonly used in mineral resource exploration. However, the weak energy of AMT signals makes them susceptible to being overwhelmed by noise, leading to erroneous geophysical interpretations. In recent years, deep learning… read more here.

Keywords: deep learning; amt signals; block attention; convolutional block ... See more keywords

Automated detection of pinworm parasite eggs using YOLO convolutional block attention module for enhanced microscopic image analysis

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recommendations! Published in 2025 at "Frontiers in Bioengineering and Biotechnology"

DOI: 10.3389/fbioe.2025.1559987

Abstract: Introduction Parasitic infections remain a major public health concern, particularly in healthcare and community settings where rapid and accurate diagnosis is essential for effective treatment and prevention. Traditional parasite detection methods rely on manual microscopic… read more here.

Keywords: detection; block attention; attention module; attention ... See more keywords

Classification of arteriovenous fistula sounds using a convolutional block attention module and long short-term memory neural network

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recommendations! Published in 2024 at "Frontiers in Physiology"

DOI: 10.3389/fphys.2024.1397317

Abstract: The assessment of vascular accessibility in patients undergoing hemodialysis is predominantly reliant on manual inspection, a method that is associated with several limitations. In this study, we propose an alternative approach by recording the acoustic… read more here.

Keywords: block attention; attention module; long short; convolutional block ... See more keywords

Few-Shot Fault Diagnosis of Rolling Bearings Using Generative Adversarial Networks and Convolutional Block Attention Mechanisms

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recommendations! Published in 2025 at "Lubricants"

DOI: 10.3390/lubricants13120515

Abstract: In modern industrial systems, diagnosing faults in the rolling bearings of high-speed rotating machinery remains a considerable challenge due to the scarcity of reliable fault samples and the inherent complexity of the diagnostic task. To… read more here.

Keywords: block attention; attention; convolutional block; rolling bearings ... See more keywords