RT‐Unet: An advanced network based on residual network and transformer for medical image segmentation
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22956
Abstract: For the past several years, semantic segmentation method based on deep learning, especially Unet, have achieved tremendous success in medical image processing. The U‐shaped topology of Unet can well solve image segmentation tasks. However, due… read more here.
Keywords: residual network; network; unet; segmentation ... See more keywords
No projection in the residual network
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DOI: 10.1007/s10586-017-1389-z
Abstract: Convolution networks continue to create state-of-the-art results in computer vision, and the Residual Network is an important milestone. In the original residual network, 1 $$\times $$× 1 convolution with stride 2 is used as the… read more here.
Keywords: residual network; projection residual; network;
Deep residual network for highly accelerated fMRI reconstruction using variable density spiral trajectory
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.02.070
Abstract: Abstract Compressed sensing has proved itself as a useful technique for accelerating time-consuming fMRI acquisition. However, its intrinsic iterative algorithm of solving optimization problems limits its practical usage. In addition, it may still suffer from… read more here.
Keywords: reconstruction; image; network; fmri reconstruction ... See more keywords
Learning crowd behavior from real data: A residual network method for crowd simulation
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.04.141
Abstract: Abstract Traditional methods of crowd evacuation simulation reduce the visual realism of crowd motion modeling due to hypothetical scenarios and rules. Data-driven methods are an effective way to enhance the visual realism of crowd simulation.… read more here.
Keywords: residual network; crowd simulation; method; simulation ... See more keywords
An improved residual network using deep fusion for identifying RNA 5-methylcytosine sites
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DOI: 10.1093/bioinformatics/btac532
Abstract: MOTIVATION 5-Methylcytosine (m5C) is a crucial post-transcriptional modification. With the development of technology, it is widely found in various RNAs. Numerous studies have indicated that m5C plays an essential role in various activities of organisms,… read more here.
Keywords: residual network; deep fusion; methylcytosine; model ... See more keywords
Image Reconstruction Based on Fused Features and Perceptual Loss Encoder-Decoder Residual Network for Space Optical Remote Sensing Images Compressive Sensing
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3069086
Abstract: Compressive sensing (CS) technology is introduced into space optical remote sensing image acquisition stage, which could make wireless image sensor network node quickly and accurately obtain images in the case of two constraints of limited… read more here.
Keywords: reconstruction; image reconstruction; loss; residual network ... See more keywords
Research on Improved Residual Network Classification Method for Defect Recognition of Thermal Battery
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DOI: 10.1109/access.2022.3217238
Abstract: Thermal battery is an ideal power supply for military applications such as artillery and ship equipment. Due to the sheet-type process of the thermal battery, various installation error defects occur in the assembly of thermal… read more here.
Keywords: recognition; residual network; battery; model ... See more keywords
Tool Wear Monitoring Based on Transfer Learning and Improved Deep Residual Network
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DOI: 10.1109/access.2022.3221994
Abstract: Considering the complex structure weight of the existing tool wear state monitoring model based on deep learning, prone to over-fitting and requiring a large amount of training data, a monitoring method based on Transfer Learning… read more here.
Keywords: residual network; network; deep residual; improved deep ... See more keywords
Leaf Disease Detection Based on Lightweight Deep Residual Network and Attention Mechanism
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3272985
Abstract: In today’s leaf disease detection, the accuracy of recognition has never been of such importance as it is now. In this aspect, leaf disease recognition method based on machine learning relies heavily on the size… read more here.
Keywords: residual network; attention mechanism; disease detection; disease ... See more keywords
Seismic Impedance Inversion Using Fully Convolutional Residual Network and Transfer Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2019.2963106
Abstract: In this letter, we use a fully convolutional residual network (FCRN) for seismic impedance inversion. After training with appropriate data, the FCRN can effectively predict impedance with high accuracy, and have good robustness against noise… read more here.
Keywords: seismic impedance; fully convolutional; impedance; residual network ... See more keywords
BRCN-ERN: A Bidirectional Reconstruction Coding Network and Enhanced Residual Network for Hyperspectral Change Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3119859
Abstract: Change detection (CD) is a hot issue in the field of remote sensing. Hyperspectral images (HSIs) contain rich spectral information and have gradually become an important data source in CD. Spectral–spatial combination is a commonly… read more here.
Keywords: residual network; network; bidirectional reconstruction; reconstruction ... See more keywords