Search Results - "supervised autoencoder"

Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images by Cheng, Jianhong, Zhao, Wei, Liu, Jin, Xie, Xingzhi, Wu, Shangjie, Liu, Liangliang, Yue, Hailin, Li, Junjian, Wang, Jianxin, Liu, Jun

“… In this study, we proposed a deep supervised autoencoder (DSAE) framework to automatically identify COVID-19 using multi-view features extracted from CT images…”
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Captured multi-label relations via joint deep supervised autoencoder by Lian, Si-ming, Liu, Jian-wei, Lu, Run-kun, Luo, Xiong-lin

“… Meanwhile, it is not advisable to suppose that multiple labels are independent of each other. Therefore, we propose the deep supervised autoencoder as a generative model…”
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Self-supervised autoencoder network for robust heart rate extraction from noisy photoplethysmogram: Applying blind source separation to biosignal analysis by Webster, Matthew B., Lee, Dongheon, Lee, Joonnyong

“… The trained network is then applied to a noisy PPG dataset collected during the daily activities of nine subjects and a surgical dataset comprising 4,681 patients…”
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A Subject-Independent Brain-Computer Interface Framework Based on Supervised Autoencoder by Ayoobi, Navid, Sadeghian, Elnaz Banan

“… Developing a subject-independent MI-BCI system to reduce the calibration phase is still challenging due to the subject-dependent characteristics of the MI signals…”
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Are you eligible? Predicting adulthood from face images via Class Specific Mean Autoencoder by Singh, Maneet, Nagpal, Shruti, Vatsa, Mayank, Singh, Richa

“…•Proposed Multi-Resolution Face Database of more than 4000 images comprising of 317 subjects, both minors and adults…”
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Single-slice Alzheimer's disease classification and disease regional analysis with Supervised Switching Autoencoders by Mendoza-Léon, Ricardo, Puentes, John, Uriza, Luis Felipe, Hernández Hoyos, Marcela

“… SSAs are revised supervised autoencoder architectures, combining unsupervised representation and supervised classification as one unified model…”
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Tree Health Assessment from UAV Images: Improving Object Detection and Classification Using Hard Negative Mining and Semi-Supervised Autoencoder by Jemaa, Hela, Bouachir, Wassim, Leblon, Brigitte, LaRocque, Armand, Haddadi, Ata, Bouguila, Nizar

“… Inventorying trees is often performed manually through fieldwork surveys, which are generally time-consuming, costly, and subject to errors…”
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Bagging Supervised Autoencoder Classifier for Credit Scoring by Abdoli, Mahsan, Akbari, Mohammad, Shahrabi, Jamal

“… models, targeting the generalization power of classification models on unseen data. In this paper, we propose the Bagging Supervised Autoencoder Classifier (BSAC…”
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A Subject-Independent Brain-Computer Interface Framework Based on Supervised Autoencoder by Ayoobi, Navid, Elnaz Banan Sadeghian

“… Developing a subject-independent MI-BCI system to reduce the calibration phase is still challenging due to the subject-dependent characteristics of the MI signals…”
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Neural models for detection and classification of brain states and transitions by Marin-Llobet, Arnau, Manasanch, Arnau, Dalla Porta, Leonardo, Torao-Angosto, Melody, Sanchez-Vives, Maria V.

“…) and a self-supervised autoencoder-based multimodal clustering algorithm. This approach distinguishes brain states such as slow oscillations, microarousals, and wakefulness with high confidence…”
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Abnormal structural and functional network topological properties associated with left prefrontal, parietal, and occipital cortices significantly predict childhood TBI-related attention deficits: A semi-supervised deep learning study by Cao, Meng, Wu, Kai, Halperin, Jeffery M., Li, Xiaobo

“…Traumatic brain injury (TBI) is a major public health concern in children. Children with TBI have elevated risk in developing attention deficits. Existing…”
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Collaborative Random Faces-Guided Encoders for Pose-Invariant Face Representation Learning by Shao, Ming, Zhang, Yizhe, Fu, Yun

“…)-guided encoders" toward this problem. The contributions of this paper are three fold. First, we propose a novel supervised autoencoder that is able to capture the high-level identity feature despite of pose variations…”
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Anomalous Sound Detection using unsupervised and semi-supervised autoencoders and gammatone audio representation by Perez-Castanos, Sergi, Naranjo-Alcazar, Javier, Zuccarello, Pedro, Cobos, Maximo

“…Anomalous sound detection (ASD) is, nowadays, one of the topical subjects in machine listening discipline…”
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Two-Stream Architecture with Contrastive and Self-Supervised Attention Feature Fusion for Error-related Potentials Classification by Garrote, Luis, Perdiz, Joao, Yasemin, Mine, Pires, Gabriel, Nunes, Urbano J.

“… Its first stage is a self-supervised autoencoder architecture with a multi-head attention layer providing relevant latent features…”
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Autoencoder-Based Approaches for Upper Limb Use Detection by Neelakandan, Parvathy, SKM, Varadhan, Balasubramanian, Sivakumar

“… A supervised autoencoder using extracted latent features for a random forest classifier…”
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