Lung cancer classification using exponential mean saturation linear unit activation function in various generative adversarial network models
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22719
Abstract: Nowadays, the mortality rate due to lung cancer increases rapidly worldwide as it can be classified only at the later stages. Early classification of lung cancer will help patients to take treatment and decrease the… read more here.
Keywords: network; adversarial network; classification; generative adversarial ... See more keywords
Multi-sequence MR image-based synthetic CT generation using a generative adversarial network for head and neck MRI-only radiotherapy.
Sign Up to like & getrecommendations! Published in 2020 at "Medical physics"
DOI: 10.1002/mp.14075
Abstract: PURPOSE The purpose of this study is to investigate the effect of different MR sequences on the accuracy of deep learning based synthetic CT (sCT) generation in the complex head and neck region. METHODS Four… read more here.
Keywords: generative adversarial; image; based synthetic; network ... See more keywords
Clinical ultra high resolution CT scans enabled by using a generative adversarial network.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.16172
Abstract: BACKGROUND Ultra-high resolution computed tomography (UHRCT) has shown great potential for the detection of pulmonary diseases. However, UHRCT scanning generally induces increases in scanning time and radiation exposure. Super resolution is a gradually prosperous application… read more here.
Keywords: ultra high; adversarial network; high resolution; generative adversarial ... See more keywords
Unsupervised medical images denoising via graph attention dual adversarial network
Sign Up to like & getrecommendations! Published in 2021 at "Applied Intelligence"
DOI: 10.1007/s10489-020-02016-4
Abstract: A lot of natural images denoising methods have been proposed, however, there are dual primary challenges for medical images denoising: 1) paired datasets are scarce and 2) medical images are often three-dimensional. In this paper,we… read more here.
Keywords: network; images denoising; medical images; adversarial network ... See more keywords
Image enhancement algorithm based on generative adversarial network in combination of improved game adversarial loss mechanism
Sign Up to like & getrecommendations! Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-07776-x
Abstract: The feed-forward architectures of recently proposed generative adversarial network can learn the non-linear mapping from low-resolution output to high-resolution output. However, this approach does not fully address the mutual dependencies of different resolution images. By… read more here.
Keywords: generative adversarial; game; image; network ... See more keywords
Conditional generative adversarial network with densely-connected residual learning for single image super-resolution
Sign Up to like & getrecommendations! Published in 2021 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-09817-2
Abstract: Recently, generative adversarial network (GAN) has been widely employed in single image super-resolution (SISR), achieving favorably good perceptual effects. However, the SR outputs generated by GAN still have some fictitious details, which are quite different… read more here.
Keywords: adversarial network; resolution; generative adversarial; single image ... See more keywords
DGCNN: deep convolutional generative adversarial network based convolutional neural network for diagnosis of COVID-19
Sign Up to like & getrecommendations! Published in 2022 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-022-12640-6
Abstract: The latest threat to global health is the coronavirus disease 2019 (COVID-19) pandemic. To prevent COVID-19, recognizing and isolating the infected patients is an essential step. The primary diagnosis method is Reverse Transcription Polymerase Chain… read more here.
Keywords: adversarial network; generative adversarial; deep convolutional; convolutional generative ... See more keywords
ML-CGAN: Conditional Generative Adversarial Network with a Meta-learner Structure for High-Quality Image Generation with Few Training Data
Sign Up to like & getrecommendations! Published in 2021 at "Cognitive Computation"
DOI: 10.1007/s12559-020-09796-4
Abstract: Since generative adversarial network (GAN) can learn data distribution and generate new samples based on the learned data distribution, it has become a research hotspot in the area of deep learning and cognitive computation. The… read more here.
Keywords: generative adversarial; meta learner; network; training data ... See more keywords
Half-scan artifact correction using generative adversarial network for dental CT
Sign Up to like & getrecommendations! Published in 2021 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2021.104313
Abstract: Half-scan image reconstruction with Parker weighting can correct motion artifacts in dental CT images taken with a slow scan-based dental CT. Since the residual half-scan artifacts in the dental CT images appear much stronger than… read more here.
Keywords: dental images; half scan; generative adversarial; network ... See more keywords
Generative Adversarial Network Based Image Augmentation for Insect Pest Classification Enhancement
Sign Up to like & getrecommendations! Published in 2019 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2019.12.406
Abstract: Abstract The application of deep neural networks in computer vision has remarkably improved the reliability of automated insect pest identification algorithms. However, to build a robust deep neural network classifier model, sufficient number of image… read more here.
Keywords: generative adversarial; image; adversarial network; augmentation ... See more keywords
Enhanced generative adversarial network for extremely imbalanced fault diagnosis of rotating machine
Sign Up to like & getrecommendations! Published in 2021 at "Measurement"
DOI: 10.1016/j.measurement.2021.109467
Abstract: Abstract Fault diagnosis is the key procedure to ensure the stability and reliability of mechanical equipment operation. Recent works show that deep learning-based methods outperform most of traditional fault diagnosis techniques. However, a practical problem… read more here.
Keywords: adversarial network; diagnosis; generative adversarial; fault diagnosis ... See more keywords