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
Fusing convolutional generative adversarial encoders for 3D printer fault detection with only normal condition signals
Sign Up to like & getrecommendations! Published in 2021 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2020.107108
Abstract: Abstract Collecting data from mechanical systems in abnormal conditions is expensive and time consuming. Consequently, fault detection approaches based on classical supervised learning working with both normal and abnormal data are not applicable in some… read more here.
Keywords: generative adversarial; detection; convolutional generative; fault detection ... See more keywords
Classification of Canker on Small Datasets Using Improved Deep Convolutional Generative Adversarial Networks
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DOI: 10.1109/access.2019.2900327
Abstract: This paper proposes a deep learning model for the classification of citrus canker that overcomes the shortcomings of traditional approaches, and the scarce number of available images for training, which have been subject to the… read more here.
Keywords: generative adversarial; deep convolutional; adversarial networks; model ... See more keywords
Parkinson’s Disease Detection Based on Spectrogram-Deep Convolutional Generative Adversarial Network Sample Augmentation
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DOI: 10.1109/access.2020.3037775
Abstract: As an essential biological feature of human beings, voiceprint is increasingly used in medical research and diagnosis, especially in identifying Parkinson’s Disease (PD). This paper proposes a Spectrogram Deep Convolutional Generative Adversarial Network (S-DCGAN) for… read more here.
Keywords: spectrogram deep; voiceprint; parkinson disease; deep convolutional ... See more keywords
CNN-RNN and Data Augmentation Using Deep Convolutional Generative Adversarial Network for Environmental Sound Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3150258
Abstract: Deep neural networks in deep learning have been widely demonstrated to have higher accuracy and distinct advantages over traditional machine learning methods in extracting data features. While convolutional neural networks (CNNs) have shown great success… read more here.
Keywords: network; classification; data augmentation; deep convolutional ... See more keywords