Retrospective respiratory motion correction in cardiac cine MRI reconstruction using adversarial autoencoder and unsupervised learning
Sign Up to like & getrecommendations! Published in 2020 at "NMR in Biomedicine"
DOI: 10.1002/nbm.4433
Abstract: The aim of this study was to develop a deep neural network for respiratory motion compensation in free‐breathing cine MRI and evaluate its performance. An adversarial autoencoder network was trained using unpaired training data from… read more here.
Keywords: adversarial autoencoder; motion; network; motion corrupted ... See more keywords
Unsupervised Deep Anomaly Detection for Medical Images Using an Improved Adversarial Autoencoder
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Digital Imaging"
DOI: 10.1007/s10278-021-00558-8
Abstract: Anomaly detection has been applied in the various disease of medical practice, such as breast cancer, retinal, lung lesion, and skin disease. However, in real-world anomaly detection, there exist a large number of healthy samples,… read more here.
Keywords: deep anomaly; anomaly detection; detection; adversarial autoencoder ... See more keywords
Generating sequential electronic health records using dual adversarial autoencoder
Sign Up to like & getrecommendations! Published in 2020 at "Journal of the American Medical Informatics Association : JAMIA"
DOI: 10.1093/jamia/ocaa119
Abstract: OBJECTIVE Recent studies on electronic health records (EHRs) started to learn deep generative models and synthesize a huge amount of realistic records, in order to address significant privacy issues surrounding the EHR. However, most of… read more here.
Keywords: dual adversarial; adversarial autoencoder; electronic health; autoencoder ... See more keywords
Perceptual Loss-Constrained Adversarial Autoencoder Networks for Hyperspectral Unmixing
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3144327
Abstract: Recently, the use of a deep autoencoder-based method in blind spectral unmixing has attracted great attention as the method can achieve superior performance. However, most autoencoder-based unmixing methods use non-structured reconstruction loss to train networks,… read more here.
Keywords: loss constrained; adversarial autoencoder; loss; perceptual loss ... See more keywords
Adversarial autoencoder for detecting anomalies in soldered joints on printed circuit boards
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DOI: 10.1117/1.jei.29.4.041013
Abstract: Abstract. The inspection of solder joints on printed circuit boards is a difficult task because defects inside the joints cannot be observed directly. In addition, because anomalous samples are rarely obtained in a general anomaly… read more here.
Keywords: circuit boards; adversarial autoencoder; joints printed; anomaly detection ... See more keywords
Semisupervised hyperspectral imagery classification based on a three-dimensional convolutional adversarial autoencoder model with low sample requirements
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Applied Remote Sensing"
DOI: 10.1117/1.jrs.14.024522
Abstract: Abstract. Although there are many state-of-the-art methods for hyperspectral classification, data deficiency is a problem that should be addressed before popularizing hyperspectral technology. To solve this problem, it is worth exploring methods based on small… read more here.
Keywords: semisupervised hyperspectral; adversarial autoencoder; dimensional convolutional; three dimensional ... See more keywords
Designing thermal radiation metamaterials via hybrid adversarial autoencoder and Bayesian optimization
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DOI: 10.1364/ol.453442
Abstract: Designing thermal radiation metamaterials is challenging especially for problems with high degrees of freedom and complex objectives. In this Letter, we develop a hybrid materials informatics approach which combines the adversarial autoencoder and Bayesian optimization… read more here.
Keywords: thermal radiation; design; designing thermal; adversarial autoencoder ... See more keywords
Extension of M Dwarf Spectra Based on Adversarial AutoEncoder
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DOI: 10.3390/universe7090326
Abstract: M dwarfs are main sequence stars and they exist in all stages of galaxy evolution. As the living fossils of cosmic evolution, the study of M dwarfs is of great significance to the understanding of… read more here.
Keywords: adversarial autoencoder; dwarf spectra; autoencoder; spectra data ... See more keywords