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A high-level feature channel attention UNet network for cholangiocarcinoma segmentation from microscopy hyperspectral images
Pathological diagnosis is the gold standard for the diagnosis of cholangiocarcinoma. The manual segmentation of pathology sections is time-consuming....
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Feature channel interaction long-tailed image classification model based on dual attention
In the real world, the data distribution often presents a long tail distribution, and the imbalance of data will lead to the model learning bias to...
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Relation-Aware Facial Expression Recognition Using Contextual Residual Network with Attention Mechanism
With the existence of occlusion or posture changes, facial expression recognition (FER) under uncontrolled conditions is difficult. To obtain a...
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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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Multi-stage strength estimation network with cross attention for single channel speech enhancement
Speech enhancement is a fundamental task for acoustic signal processing, which is still an unsolved challenge. Recently, with the rapid development...
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Combining Non-local Sparse and Residual Channel Attentions for Single Image Super-resolution Across Modalities
Single image super-resolution (SISR) is an ill-posed problem that aims to generate a high-resolution (HR) image from a single low-resolution (LR)...
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4RATFNet: Four-Dimensional Residual-Attention Improved-Transfer Few-Shot Semantic Segmentation Network for Landslide Detection
Landslides are hazardous and in many cases can cause enormous economic losses and human casualties. The suddenness of landslides makes it difficult...
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Residual deep gated recurrent unit-based attention framework for human activity recognition by exploiting dilated features
Human activity recognition (HAR) in video streams becomes a thriving research area in computer vision and pattern recognition. Activity recognition...
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Low-light image enhancement using transformer with color fusion and channel attention
Low-light image enhancement aims to optimize images captured in low-light conditions with low brightness and contrast, rendering them natural-looking...
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Enhancing EfficientNetv2 with global and efficient channel attention mechanisms for accurate MRI-Based brain tumor classification
The early and accurate diagnosis of brain tumors is critical for effective treatment planning, with Magnetic Resonance Imaging (MRI) serving as a key...
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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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Estimation of cattle weight from composite image/height/length data with spatial and channel attention convolution network (SCA-ConvNet)
Currently, the predominant method for indirectly obtaining cattle weight data involves establishing the correlation between cattle liveweight and...
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STRAN: Student expression recognition based on spatio-temporal residual attention network in classroom teaching videos
In order to obtain the state of students’ listening in class objectively and accurately, we can obtain students’ emotions through their expressions...
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HEU-Net: hybrid attention residual block-based network with external skip connections for metal corrosion semantic segmentation
Regularly detect the corrosion of metal structures and take countermeasures according to the degree of corrosion, which can reduce the potential...
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M-AResNet: a novel multi-scale attention residual network for melting curve image classification
Melting curve image is a hallmark of quantitative polymerase chain reaction and is a crucial indicator for the validity of the cycle threshold....
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Dynamic Gesture Recognition Based on 3D Central Difference Separable Residual LSTM Coordinate Attention Networks
The recognition of dynamic gestures has garnered significant attention in the field of human-computer interaction. However, several factors unrelated...
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Attention-Residual Convolutional Neural Network for Image Restoration Due to Bad Weather
Image quality degrades due to various reasons. In some circumstances, different weather conditions like fog, mist or rain have an impact on image...
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Residual spatial graph convolution and temporal sequence attention network for sign language translation
Vision-based sign language translation technology (SLT) has brought the communication distance between deaf and ordinary people closer to a certain...
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A temporal and channel-combined attention block for action segmentation
The task of video action segmentation is to classify an untrimmed long video at the frame level. With the requirement of processing long-term feature...
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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...
