Suchergebnisse - "Conditional variational autoencoders"

3D High-Resolution Cardiac Segmentation Reconstruction From 2D Views Using Conditional Variational Autoencoders von Biffi, Carlo, Cerrolaza, Juan J., Tarroni, Giacomo, de Marvao, Antonio, Cook, Stuart A., O'Regan, Declan P., Rueckert, Daniel

“… To address this, we propose a conditional variational autoencoder architecture able to learn a generative model of 3D high-resolution left ventricular (LV …”
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3D High-Resolution Cardiac Segmentation Reconstruction from 2D Views using Conditional Variational Autoencoders von Biffi, Carlo, Cerrolaza, Juan J, Tarroni, Giacomo, de Marvao, Antonio, Cook, Stuart A, O'Regan, Declan P, Rueckert, Daniel

“… To address this, we propose a conditional variational autoencoder architecture able to learn a generative model of 3D high-resolution left ventricular (LV …”
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Sensing anomaly of photovoltaic systems with sequential conditional variational autoencoder von Li, Ding, Zhang, Yufei, Yang, Zheng, Jin, Yaohui, Xu, Yanyan

“… This study proposes the Sequential Conditional Variational Autoencoder (SCVAE), which can cope with the sequential impacts of the environment on PV …”
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Generation of 12-Lead Electrocardiogram with Subject-Specific, Image-Derived Characteristics Using a Conditional Variational Autoencoder von Sang, Yuling, Beetz, Marcel, Grau, Vicente

“… ). Among these, deep generative models have shown their ability in ECG generation. In this paper, we propose a conditional variational autoencoder (cVAE …”
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Learning a Probabilistic Model for Diffeomorphic Registration von Krebs, Julian, Delingette, Herve, Mailhe, Boris, Ayache, Nicholas, Mansi, Tommaso

“… image. Our unsupervised method is based on the variational inference. In particular, we use a conditional variational autoencoder network and constrain transformations to be symmetric …”
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Brain fingerprinting and cognitive behavior predicting using functional connectome of high inter-subject variability von Lu, Jiayu, Yan, Tianyi, Yang, Lan, Zhang, Xi, Li, Jiaxin, Li, Dandan, Xiang, Jie, Wang, Bin

“… •High inter-subject variability for brain fingerprinting and cognitive behavior predicting …”
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Spherical Image Generation From a Few Normal-Field-of-View Images by Considering Scene Symmetry von Hara, Takayuki, Mukuta, Yusuke, Harada, Tatsuya

“… Spherical images taken in all directions (360 degrees by 180 degrees) can represent an entire space including the subject, providing free direction viewing and an immersive experience to viewers …”
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Learning a Generative Motion Model From Image Sequences Based on a Latent Motion Matrix von Krebs, Julian, Delingette, Herve, Ayache, Nicholas, Mansi, Tommaso

“… allowing for faster data acquisition and data augmentation. More precisely, the motion matrix allows to transport the recovered motion from one subject to another …”
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A deep learning-based pipeline for developing multi-rib shape generative model with populational percentiles or anthropometrics as predictors von Huang, Yuan, Holcombe, Sven A., Wang, Stewart C., Tang, Jisi

“… Rib cross-sectional shapes (characterized by the outer contour and cortical bone thickness) affect the rib mechanical response under impact loading, thereby …”
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Heartbeat detection and personal authentication using a 60 GHz Doppler sensor von Asano, Takuma, Izumi, Shintaro, Kawaguchi, Hiroshi

“… We proposed a method for authenticating and identifying heartbeat signals through supervised learning using a conditional variational autoencoder (CVAE). A 60 …”
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Individualizing Head-Related Transfer Functions for Binaural Acoustic Applications von Zandi, Navid H., El-Mohandes, Awny M., Zheng, Rong

“… Accurate estimations of HRTFs for human subjects are crucial in enabling binaural acoustic applications such as sound localization and 3D sound spatialization …”
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Individualized multi-horizon MRI trajectory prediction for Alzheimer's Disease von He, Rosemary, Ang, Gabriella, Tward, Daniel

“… Here we turn to conditional variational autoencoders to generate individualized MRI predictions given the subject's age, disease status and one previous scan …”
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Spherical Image Generation from a Single Normal Field of View Image by Considering Scene Symmetry von Hara, Takayuki, Harada, Tatsuya

“… Spherical images taken in all directions (360 degrees) allow representing the surroundings of the subject and the space itself, providing an immersive experience to the viewers …”
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Attacks on state-of-the-art face recognition using attentional adversarial attack generative network von Yang, Lu, Song, Qing, Wu, Yingqi

“… Therefore, it is very important to study how face recognition networks are subject to attacks …”
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Conditional VAE for personalized neurofeedback in cognitive training von Tibermacine, Imad Eddine, Russo, Samuele, Scarano, Gianmarco, Tedesco, Giancarlo, Rabehi, Abdelaziz, Alhussan, Amel Ali, Khafaga, Doaa Sami, Eid, Marwa M., El-kenawy, El-Sayed M., Napoli, Christian

“… In this work, we explore the use of a Conditional Variational Autoencoder (CVAE) that injects a binary health label …”
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AI-Based Localized Latent Neural Representations of Acute and Chronic Pain in Rats von Yao, Dunyan, Lloyd, David A., Akay, Yasemin, Ohsawa, Masahiro, Akay, Metin

“… Chronic pain is a widespread phenomenon affecting over 21% of the United States population. Despite the significant impact of pain on a patient's quality of …”
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Deep conditional generative model for personalization of 12-lead electrocardiograms and cardiovascular risk prediction von Sang, Yuling, Banerjee, Abhirup, Beetz, Marcel, Grau, Vicente

“… We propose a conditional Variational Autoencoder (cVAE) framework to generate realistic, subject-specific 12-lead ECGs …”
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Classification of EEG Signal Using Deep Learning Architectures Based Motor-Imagery for an Upper-Limb Rehabilitation Exoskeleton von Titkanlou, Maryam Khoshkhooy, Pham, Duc Thien, Mouček, Roman

“… Three different methods, including noise injection (NI), conditional variational autoencoder (cVAE …”
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Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders von Ozdenizci, Ozan, Wang, Ye, Koike-Akino, Toshiaki, Erdogmus, Deniz

“… ). The proposed approach aims to learn subject-invariant representations by simultaneously training a conditional variational autoencoder (cVAE …”
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DeepComBat: A Statistically Motivated, Hyperparameter-Robust, Deep Learning Approach to Harmonization of Neuroimaging Data von Hu, Fengling, Lucas, Alfredo, Chen, Andrew A, Coleman, Kyle, Horng, Hannah, Ng, Raymond W S, Tustison, Nicholas J, Davis, Kathryn A, Shou, Haochang, Li, Mingyao, Shinohara, Russell T

“… Neuroimaging data from multiple batches (i.e. acquisition sites, scanner manufacturer, datasets, etc.) are increasingly necessary to gain new insights into the …”
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