Suchergebnisse - "variational autoencoder (VAE)"

Spatio-Temporal Classification of Lung Ventilation Patterns Using 3D EIT Images: A General Approach for Individualized Lung Function Evaluation von Chen, Shuzhe, Li, Li, Lin, Zhichao, Zhang, Ke, Gong, Ying, Wang, Lu, Wu, Xu, Li, Maokun, Song, Yuanlin, Yang, Fan, Xu, Shenheng

“… The study uses a Variational Autoencoder (VAE) with a MultiRes block to compress the spatial distribution in a 3D image into a one …”
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Cross-Modal Information Recovery and Enhancement Using Multiple-Input-Multiple-Output Variational Autoencoder von Liang, Jessica E.

“… ) variational autoencoder (VAE) and subsequently apply it to cross-modal information recovery and enhancement …”
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Deep Variational Autoencoder for Mapping Functional Brain Networks von Qiang, Ning, Dong, Qinglin, Ge, Fangfei, Liang, Hongtao, Ge, Bao, Zhang, Shu, Sun, Yifei, Gao, Jie, Liu, Tianming

“… In the neuroimaging and brain mapping communities, researchers have proposed a variety of computational methods to map functional brain networks (FBNs) …”
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Subject-invariant feature learning for mTBI identification using LSTM-based variational autoencoder with adversarial regularization von Salsabilian, Shiva, Najafizadeh, Laleh

“… ) combines the representation learning ability of the variational autoencoder (VAE) with the temporal modeling characteristics of the LSTM to learn the latent space representations from neural activity …”
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Quantifying the spatial patterns of retinal ganglion cell loss and progression in optic neuropathy by applying a deep learning variational autoencoder approach to optical coherence tomography von Wang, Jui-Kai, Johnson, Brett A., Chen, Zhi, Zhang, Honghai, Szanto, David, Woods, Brian, Wall, Michael, Kwon, Young H., Linton, Edward F., Pouw, Andrew, Kupersmith, Mark J., Garvin, Mona K., Kardon, Randy H.

“… Glaucoma, optic neuritis (ON), and non-arteritic anterior ischemic optic neuropathy (NAION) produce distinct patterns of retinal ganglion cell (RGC) damage. We …”
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An Interpretable Generative Model for Handwritten Digits Synthesis von Zhu, Yao, Suri, Saksham, Kulkarni, Pranav, Chen, Yueru, Duan, Jiali, Kuo, C.-C. Jay

“… Modern image generative models such as the variational autoencoder (VAE) are trained by backpropagation (BP …”
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Improving Motor Imagery EEG Signal Classification Using Deep Learning Techniques von Velakanti, Gouthami, Mahveen, Safa, Rao, A. Abhinav, Sai Hanith, M., Priya, G. Krishna, Sushrith Reddy, K.

“… -to-noise ratio, inter-subject variability, and the presence of physiological artifacts. This study proposes an innovative deep learning architecture that harmoniously integrates a Variational Autoencoder (VAE …”
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Variational autoencoder-based estimation of chronological age and changes in morphological features of teeth von Joo, Subin, Jung, Won, Oh, Seung Eel

“… This study led to the development of a variational autoencoder (VAE) for estimating the chronological age of subjects using feature values extracted from their teeth …”
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PCovNet+: A CNN-VAE anomaly detection framework with LSTM embeddings for smartwatch-based COVID-19 detection von Abir, Farhan Fuad, Chowdhury, Muhammad E.H., Tapotee, Malisha Islam, Mushtak, Adam, Khandakar, Amith, Mahmud, Sakib, Hasan, Anwarul

“…  al. (2020), the study’s first phase included a cohort of 5,262 subjects, with 3,325 Fitbit users constituting the majority …”
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Separating group- and individual-level brain signatures in the newborn functional connectome: A deep learning approach von Kim, Jung-Hoon, De Asis-Cruz, Josepheen, Limperopoulos, Catherine

“… •The VAE shows significant subject identification accuracy with whole-brain FC profiles, surpassing the identification accuracy obtained with linear countermodels …”
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Efficacy of Smoothing Algorithms to Enhance Detection of Visual Field Progression in Glaucoma von Mohammadzadeh, Vahid, Li, Leyan, Fei, Zhe, Davis, Tyler, Morales, Esteban, Wu, Kara, Lee Ma, Elise, Afifi, Abdelmonem, Nouri-Mahdavi, Kouros, Caprioli, Joseph

“… To evaluate and compare the effectiveness of nearest neighbor (NN)- and variational autoencoder (VAE …”
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Data Augmentation for Motor Imagery Signal Classification Based on a Hybrid Neural Network von Zhang, Kai, Xu, Guanghua, Han, Zezhen, Ma, Kaiquan, Zheng, Xiaowei, Chen, Longting, Duan, Nan, Zhang, Sicong

“… Due to the strict requirements for subjects and experimental environments, it is difficult to collect large-scale and high-quality electroencephalogram (EEG) data …”
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Image fragmented learning for data-driven topology design von Yang, Yusibo, Yaji, Kentaro, Yamasaki, Shintaro, Fujita, Kikuo

“… This paper proposes a data-driven topology design (DDTD) framework, incorporating image fragmented learning that leverages the technique of dividing an image …”
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StRegA: Unsupervised anomaly detection in brain MRIs using a compact context-encoding variational autoencoder von Chatterjee, Soumick, Sciarra, Alessandro, Dünnwald, Max, Tummala, Pavan, Agrawal, Shubham Kumar, Jauhari, Aishwarya, Kalra, Aman, Oeltze-Jafra, Steffen, Speck, Oliver, Nürnberger, Andreas

“… Expert interpretation of anatomical images of the human brain is the central part of neuroradiology. Several machine learning-based techniques have been …”
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Enhancing biomechanical machine learning with limited data: generating realistic synthetic posture data using generative artificial intelligence von Dindorf, Carlo, Dully, Jonas, Konradi, Jürgen, Wolf, Claudia, Becker, Stephan, Simon, Steven, Huthwelker, Janine, Werthmann, Frederike, Kniepert, Johanna, Drees, Philipp, Betz, Ulrich, Fröhlich, Michael

“… A Variational Autoencoder (VAE) architecture was employed to generate and evaluate synthetic posture data, examining its distinguishability from real data by domain experts, ML classifiers, and Statistical Parametric Mapping (SPM …”
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InstantGroup: Instant Template Generation for Scalable Group of Brain MRI Registration von He, Ziyi, Chung, Albert C. S.

“… In this paper, we present InstantGroup, an efficient groupwise template generation framework based on variational autoencoder (VAE …”
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RePaint High-Density Surface Electromyography Signal Using Denoising Diffusion Probabilistic Model von Zhao, Yihui, Liao, Jiawei, Fang, Xia, Wang, Hai, Jiang, Ning, He, Jiayuan

“… Objective: High-density surface electromyography (HD-sEMG) has emerged as a powerful tool for myoelectric control and activation pattern analysis. However, …”
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Generation of short-term follow-up chest CT images using a latent diffusion model in COVID-19 von Kawata, Naoko, Iwao, Yuma, Matsuura, Yukiko, Higashide, Takashi, Okamoto, Takayuki, Sekiguchi, Yuki, Nagayoshi, Masaru, Takiguchi, Yasuo, Suzuki, Takuji, Haneishi, Hideaki

“… The image underwent variational autoencoder (VAE) encoding, resulting in latent vectors. The information …”
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AD-VAE: Adversarial Disentangling Variational Autoencoder von Silva, Adson, Farias, Ricardo

“… However, in Single Sample Per Person Face Recognition (SSPP FR), the challenge of learning robust and discriminative features that preserve the subject’s identity persists …”
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VAE-CapsNet: A common emotion information extractor for cross-subject emotion recognition von Chen, Huayu, Li, Junxiang, He, Huanhuan, Sun, Shuting, Zhu, Jing, Li, Xiaowei, Hu, Bin

“… To address these challenges, we propose a novel common emotion information extraction framework VAE-CapsNet that combines a variational autoencoder (VAE …”
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