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Attention-based multi-scale recursive residual network for low-light image enhancement
Aiming at the problems of color distortion, low image processing efficiency, rich context information, spatial information imbalance in the current...
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FEMRNet: Feature-enhanced multi-scale residual network for image denoising
Deep convolutional neural networks (DCNN) have attracted considerable interest in image denoising because of their excellent learning capacity....
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Smoke semantic segmentation with multi-scale residual paths and weighted middle surveillances
Visual smoke segmentation is widely used for fire detection, simulation, human evacuation and pollution monitoring. However, it is challenging to...
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FMR-Net: a fast multi-scale residual network for low-light image enhancement
The low-light image enhancement algorithm aims to solve the problem of poor contrast and low brightness of images in low-light environments. Although...
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MSARN: A Multi-scale Attention Residual Network for End-to-End Environmental Sound Classification
In current end-to-end environmental sound classification model, fixed-size filters are difficult to balance the time-frequency resolution while the...
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Aircraft segmentation in remote sensing images based on multi-scale residual U-Net with attention
Aircraft segmentation in remote sensing images (RSIs) is an important but challenging problem for both civil and military applications. U-Net and its...
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Dual parallel multi-scale residual overlay network for single-image rain removal
Rain not only degrades the perceptual image quality, but also destroys the visibility of the scene, which affects the computer vision algorithms’...
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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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Fusing Multi-scale Residual Network for Skeleton Detection
The skeleton is an important topological description of the object’s geometric form. As an advanced feature, the object skeleton information...
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Multi-scale Information Fusion Combined with Residual Attention for Text Detection
Driven by deep learning and neural networks, text detection technology has made further developments. Due to the complexity and diversity of scene...
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A multi-scale residual capsule network for hyperspectral image classification with small training samples
Convolutional Neural Network(CNN) has been widely employed in hyperspectral image(HSI) classification. However, CNN cannot attain the relative...
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A multi-modal lecture video indexing and retrieval framework with multi-scale residual attention network and multi-similarity computation
Due to technological development, the mass production of video and its storage on the Internet has increased. This made a huge amount of videos to be...
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Residual attention mechanism and weighted feature fusion for multi-scale object detection
Object detection is one of the critical problems in computer vision research, which is also an essential basis for understanding high-level semantic...
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A Multi-scale Dilated Residual Convolution Network for Image Denoising
Due to the excellent performance of deep learning, more and more image denoising methods based on convolutional neural networks (CNN) are proposed,...
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Multi-scale Residual Interaction for RGB-D Salient Object Detection
RGB-D salient object detection (SOD) is used to detect the most attractive object in the scene. There is a problem in front of the existing RGB-D SOD...
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Image steganalysis with multi-scale residual network
In recent years, many deep neural network models are used in steganalysis. However, the deep neural network models on steganalysis usually use the...
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A residual multi-scale feature extraction network with hybrid loss for low-dose computed tomography image denoising
In order to suppress noise and artifacts in low-dose computed tomography (LDCT), various deep learning techniques, especially encoder-decoder...
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SiamMaskAttn: inverted residual attention block fusing multi-scale feature information for multitask visual object tracking networks
Multitask learning combining visual object tracking and other computer vision tasks has received increasing attention from researchers. Among them,...
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An efficient multimodal sentiment analysis in social media using hybrid optimal multi-scale residual attention network
Sentiment analysis is a key component of many social media analysis projects. Additionally, prior research has concentrated on a single modality in...
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Automatic fish counting via a multi-scale dense residual network
The existing fish counting methods count the number of fish through target detection or regression, and these methods are difficult to process the...
