Aspect-based sentiment classification with multi-attention network
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.01.024
Abstract: Abstract Aspect-based sentiment classification aims to predict the sentiment polarity of an aspect term in a sentence instead of the sentiment polarity of the entire sentence. Neural networks have been used for this task, and… read more here.
Keywords: based sentiment; multi attention; sentiment; aspect based ... See more keywords
ID-insensitive deepfake detection model based on multi-attention mechanism
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-96254-6
Abstract: Deepfake technology has enabled the widespread distribution of manipulated facial content online, raising serious societal concerns. In recent years, deepfake detection has emerged as a critical research focus. However, existing methods frequently overlook the connection… read more here.
Keywords: detection; detection model; attention; attention mechanism ... See more keywords
Intelligent fault diagnosis of double-aligned domain adaptation based on multi-structure fusion and multi-attention mechanism
Sign Up to like & getrecommendations! Published in 2024 at "Measurement Science and Technology"
DOI: 10.1088/1361-6501/ad21d0
Abstract: Currently, most fault diagnosis methods based on domain adaptation (DA) reduce the distribution discrepancy between the source and target domains by aligning their high-dimensional features, but do not consider the impact of the source domain… read more here.
Keywords: multi structure; structure fusion; attention mechanism; double aligned ... See more keywords
A lightweight rail surface defect detection algorithm integrating multi-attention mechanism and content-aware reassembly of features
Sign Up to like & getrecommendations! Published in 2025 at "Measurement Science and Technology"
DOI: 10.1088/1361-6501/adfe08
Abstract: Rail surface defect inspection and maintenance play a crucial role in ensuring the safety of railway operations. While existing deep learning-based lightweight detection methods have enhanced the efficiency of manual inspections, their performance remains less… read more here.
Keywords: detection; surface defect; rail surface; content aware ... See more keywords
Defects Inspection in Polycrystalline Solar Cells Electroluminescence Images Using Deep Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2976843
Abstract: Solar cells defects inspection plays an important role to ensure the efficiency and lifespan of photovoltaic modules. However, it is still an arduous task because of the diverse attributes of electroluminescence images, such as indiscriminative… read more here.
Keywords: solar cells; electroluminescence images; attention; defects inspection ... See more keywords
MAGRes-UNet: Improved Medical Image Segmentation Through a Deep Learning Paradigm of Multi-Attention Gated Residual U-Net
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3374108
Abstract: Precise segmentation is vital for successful diagnosis and treatment planning. Medical image segmentation has demonstrated remarkable advances with the introduction of deep convolutional neural networks, particularly encoder-decoder networks such as U-Net. Despite their excellent performances,… read more here.
Keywords: segmentation; multi attention; magres unet; medical image ... See more keywords
Dual Backbone Multi-Attention Hierarchical Fusion and Feature Enhancement Network for Crowd Counting
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Consumer Electronics"
DOI: 10.1109/tce.2025.3557449
Abstract: In recent years, significant progress has been made in crowd counting with the development of convolutional neural networks (CNNs). However, while CNNs excel at extracting local features, their limited receptive fields restrict their ability to… read more here.
Keywords: crowd counting; backbone; dual backbone; network ... See more keywords
MATNet: A Combining Multi-Attention and Transformer Network for Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3254523
Abstract: Hyperspectral image (HSI) has rich spatial–spectral information, high spectral correlation, and large redundancy between information. Due to the sparse background distribution of HSI, the existing methods generally perform poorly for the classification of class pixels… read more here.
Keywords: network; matnet; classification; multi attention ... See more keywords
MAS-DSO: Advancing Direct Sparse Odometry With Multi-Attention Saliency
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2024.3414171
Abstract: Visual odometry (VO) is a critical component of simultaneous localization and mapping (SLAM) with extensive applications in robot navigation and beyond. However, prevalent VO methods often underperform in intricate environments with dynamic textures, insufficient lighting,… read more here.
Keywords: odometry; mas dso; saliency; multi attention ... See more keywords
MAFA-Uformer: Multi-attention and dual-branch feature aggregation U-shaped transformer for sparse-view CT reconstruction
Sign Up to like & getrecommendations! Published in 2025 at "Journal of X-Ray Science and Technology"
DOI: 10.1177/08953996241300016
Abstract: Background Although computed tomography (CT) is widely employed in disease detection, X-ray radiation may pose a risk to the health of patients. Reducing the projection views is a common method, however, the reconstructed images often… read more here.
Keywords: branch; attention; sparse view; dual branch ... See more keywords
Multi-Attention-Guided Cascading Network for End-to-End Person Search
Sign Up to like & getrecommendations! Published in 2023 at "Applied Sciences"
DOI: 10.3390/app13095576
Abstract: The key procedure is to accurately identify pedestrians in complex scenes and effectively embed features from multiple vision cues. However, it is still a limitation to coordinate two tasks in the unified framework, thus leading… read more here.
Keywords: network; multi attention; person search; search ... See more keywords