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Image Super-Resolution Based on Adaptive Feature Fusion Channel Attention
Since the advent of SENet, existing image super-resolution models based on deep learning have been keen to improve networks’ cross-channel...
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Aero-engine remaining useful life prediction based on a long-term channel self-attention network
The accurate prediction of remaining useful life (RUL) is conducive to reducing equipment failure rates and maintenance costs. As the long-term...
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NResNet: nested residual network based on channel and frequency domain attention mechanism for speaker verification in classroom
With the development of deep learning technology, the pattern of artificial intelligence in education has attracted more and more attention. However,...
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Performance-Efficiency Comparisons of Channel Attention Modules for ResNets
Attention modules can be added to neural network architectures to improve performance. This work presents an extensive comparison between several...
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Spatio-Channel Attention Blocks for Cross-modal Crowd Counting
Crowd counting research has made significant advancements in real-world applications, but it remains a formidable challenge in cross-modal settings....
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Pyramid Channel Attention Combined Adaptive Multi-column Network for SISR
Deep convolutional neural networks (CNN) have achieved excellent performance in the single image super-resolution (SISR) task. Blindly stacking...
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AFF-CAM: Adaptive Frequency Filtering Based Channel Attention Module
Locality from bounded receptive fields is one of the biggest problems that needs to be solved in convolutional neural networks. Meanwhile, operating...
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HTC-Net: Hashimoto’s thyroiditis ultrasound image classification model based on residual network reinforced by channel attention mechanism
Convolutional neural network (CNN) is efficient in extracting and aggregating local features in the spatial dimension of the images. However,...
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Dual-channel and multi-granularity gated graph attention network for aspect-based sentiment analysis
The Aspect-Based Sentiment Analysis(ABSA) aims to determine the sentiment polarity of a specific aspect. Existing approaches use graph attention...
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Patches Channel Attention for Human Sitting Posture Recognition
Individuals frequently maintain poor posture for extended periods while engrossed in their work, leading to potential health risks. Consequently,...
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Channel and spatial attention-guided network for deep high dynamic range imaging with large motions
Multi-exposure fusion (MEF) is widely researched and applied to high dynamic range (HDR) imaging, where one of the most challenging problems is the...
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CAWNet: A Channel Attention Watermarking Attack Network Based on CWABlock
In recent years, watermarking technology has been widely used as a common information hiding technique in the fields of copyright protection,...
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DC-CNN: Dual-channel Convolutional Neural Networks with attention-pooling for fake news detection
Fake news detection mainly relies on the extraction of article content features with neural networks. However, it has brought some challenges to...
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MPCSAN: multi-head parallel channel-spatial attention network for facial expression recognition in the wild
Facial expression recognition (FER) in the wild is an exceedingly challenging task in computer vision due to subtle differences, poses, occlusions,...
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Infrared-visible person re-identification via Dual-Channel attention mechanism
Infrared-Visible person re-identification (IV-ReID) is really a challenging task, which aims to match pedestrian images captured by visible and...
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GSCA-Net: A Global Spatial Channel Attention Network for Kidney, Tumor and Cyst Segmentation
Automatic segmentation of the kidney, tumor, and cysts is crucial for the treatment of renal cancer. In this paper, we employed a 3D residual U-Net...
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TCS-LipNet: Temporal & Channel & Spatial Attention-Based Lip Reading Network
Lip-reading is the process of translating input lip-movement image sequences into text sequences, which is a task that requires both temporal and...
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RCSLFNet: a novel real-time pedestrian detection network based on re-parameterized convolution and channel-spatial location fusion attention for low-resolution infrared image
A novel real-time infrared pedestrian detection algorithm is introduced in this study. The proposed approach leverages re-parameterized convolution...
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Prioritized air light and transmittance extraction (PATE) using dual weighted deep channel and spatial attention based model for image dehazing
The image dehazing is a complicated dilemma to resolve the haze density influence on the object depth. Though many pixel-based or color space-based...
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MSSD: multi-scale object detector based on spatial pyramid depthwise convolution and efficient channel attention mechanism
Object detection has made widespread development and remarkable progress in various fields, but, in complex application scenarios, often encounters...
