Výsledky vyhledávání - "autoencoder"

The shape variational autoencoder: A deep generative model of part‐segmented 3D objects Autor Nash, C., Williams, C. K. I.

“…We introduce a generative model of part‐segmented 3D objects: the shape variational auto‐encoder (ShapeVAE). The ShapeVAE describes a joint distribution over…”
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Integrate multi-omics data with biological interaction networks using Multi-view Factorization AutoEncoder (MAE) Autor Ma, Tianle, Zhang, Aidong

“… Results We developed a method called Multi-view Factorization AutoEncoder (MAE) with network constraints that can seamlessly integrate multi-omics data and domain…”
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Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction Autor Han, Mo, Ozdenizci, Ozan, Wang, Ye, Koike-Akino, Toshiaki, Erdogmus, Deniz

“… Results on cross-subject transfer evaluations exhibit the benefits of the proposed framework, with up to <inline-formula><tex-math notation="LaTeX">8.8\%</tex-math></inline-formula> improvement in average accuracy of classification, and demonstrate adaptability to a broader range of subjects…”
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Representation learning of resting state fMRI with variational autoencoder Autor Kim, Jung-Hoon, Zhang, Yizhen, Han, Kuan, Wen, Zheyu, Choi, Minkyu, Liu, Zhongming

“…•Variational auto-encoder disentangles generative factors of resting state fMRI activity.•Variational auto-encoder trained with unsupervised learning extracts…”
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Variational autoencoder: An unsupervised model for encoding and decoding fMRI activity in visual cortex Autor Han, Kuan, Wen, Haiguang, Shi, Junxing, Lu, Kun-Han, Zhang, Yizhen, Fu, Di, Liu, Zhongming

“…) from three human subjects passively watching natural videos. Compared to CNN, VAE could predict the video-evoked cortical responses with comparable accuracy in early visual areas, but relatively lower accuracy in higher-order visual areas…”
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MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer’s disease progression modelling Autor Martí-Juan, Gerard, Lorenzi, Marco, Piella, Gemma

“…•A multi-channel model based on recurrent variational autoencoders was proposed to capture spatial and temporal evolution of AD using multimodal data…”
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Autoencoder based self-supervised test-time adaptation for medical image analysis Autor He, Yufan, Carass, Aaron, Zuo, Lianrui, Dewey, Blake E., Prince, Jerry L.

“…•Quick test-time adaptation to a single test subject at inference stage.•Applicable to both medical image synthesis and segmentation. [Display omitted…”
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AD-VAE: Adversarial Disentangling Variational Autoencoder Autor 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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An extended variational autoencoder for cross-subject electromyograph gesture recognition Autor Zhang, Zhen, Ming, Yuewei, Shen, Quming, Wang, Yanyu, Zhang, Yuhui

“… However, cross-subject tasks remain challenging due to inherent individual differences. To address this, a novel approach for hand gesture recognition is proposed that leverages a subject-generalized variational autoencoder…”
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Reducing variations in multi-center Alzheimer’s disease classification with convolutional adversarial autoencoder Autor Cobbinah, Bernard M., Sorg, Christian, Yang, Qinli, Ternblom, Arvid, Zheng, Changgang, Han, Wei, Che, Liwei, Shao, Junming

“…Based on brain magnetic resonance imaging (MRI), multiple variations ranging from MRI scanners to center-specific parameter settings, imaging protocols, and…”
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AutoEncoder Filter Bank Common Spatial Patterns to decode Motor Imagery from EEG Autor Mammone, Nadia, Ieracitano, Cosimo, Adeli, Hojjat, Morabito, Francesco C.

“…) algorithm, named AutoEncoder(AE)-FBCSP, to benefit from the ability of AE to learn how to map data from the feature space onto a latent space where information relevant for classification are is embedded…”
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Adaptive denoising autoencoder for robust fault detection Autor Li, Zixuan, Zhao, Haitao

“…In real chemical processes, the collected data is often subject to interference from ambient environmental noise, resulting in a decline in the detection performance…”
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mmFall: Fall Detection Using 4-D mmWave Radar and a Hybrid Variational RNN AutoEncoder Autor Jin, Feng, Sengupta, Arindam, Cao, Siyang

“…) a hybrid variational recurrent neural network (RNN) autoencoder (HVRAE) to compute the anomaly level of the body motion based on the acquired point cloud…”
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EEG-Based Personal Identification by Special Design Domain-Adaptive Autoencoder Autor Oztemel, Muhammed Esad, Soysal, Ömer Muhammet

“… Autoencoders are well-known machine learning models that automate feature extraction, which is a crucial step in biometric identification…”
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Functional connectome fingerprinting: Identifying individuals and predicting cognitive functions via autoencoder Autor Cai, Biao, Zhang, Gemeng, Zhang, Aiying, Xiao, Li, Hu, Wenxing, Stephen, Julia M., Wilson, Tony W., Calhoun, Vince D., Wang, Yu‐Ping

“… regarded as “brain fingerprinting” to identify an individual from a pool of subjects. Both common and unique information has been shown to exist in the connectomes across individuals…”
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CAE-MAS: Convolutional Autoencoder Interference Cancellation for Multiperson Activity Sensing With FMCW Microwave Radar Autor Raeis, Hossein, Kazemi, Mohammad, Shirmohammadi, Shervin

“… Frequency-modulated continuous-wave (FMCW) radars can be used for target tracking, but their collected data are usually accompanied by a significant amount of interference, especially in indoor environments hosting multiple human subjects…”
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Parameterized Gompertz-Guided Morphological AutoEncoder for Predicting Pulmonary Nodule Growth Autor Fang, Jiansheng, Wang, Jingwen, Li, Anwei, Yan, Yuguang, Liu, Hongbo, Li, Jiajian, Yang, Huifang, Hou, Yonghe, Yang, Xuening, Yang, Ming, Liu, Jiang

“…The growth rate of pulmonary nodules is a critical clue to the cancerous diagnosis. It is essential to monitor their dynamic progressions during pulmonary…”
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Estimation of Fugl–Meyer Assessment Upper-Extremity Sub-Scores Using a Mixup-Augmented LSTM Autoencoder and Wearable Sensor Data Autor Liu, Minghao, Lu, Hsuan-Yu, Tong, Shuk-Fan, Liang, Dezhi, Sun, Haoyuan, Xing, Tian, Shi, Xiangqian, Yu, Hongliu, Tong, Raymond Kai-Yu

“…Stroke is a leading cause of long-term disability worldwide, necessitating efficient motor function assessment to guide personalized rehabilitation. The…”
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ASD-SAENet: A Sparse Autoencoder, and Deep-Neural Network Model for Detecting Autism Spectrum Disorder (ASD) Using fMRI Data Autor Almuqhim, Fahad, Saeed, Fahad

“… In this paper, we developed a deep-learning model called ASD-SAENet for classifying patients with ASD from typical control subjects using fMRI data…”
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Optimizing sEMG Gesture Recognition with Stacked Autoencoder Neural Network for Bionic Hand Autor Yadav, Mr. Amol Pandurang, Patil, Dr. Sandip.R.

“…This study presents a novel deep learning approach for surface electromyography (sEMG) gesture recognition using stacked autoencoder neural network…”
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