Suchergebnisse - "denoising autoencoder (DAE)"

Deep learning-based motion artifact removal in functional near-infrared spectroscopy von Gao, Yuanyuan, Chao, Hanqing, Cavuoto, Lora, Yan, Pingkun, Kruger, Uwe, Norfleet, Jack E., Makled, Basiel A., Schwaitzberg, Steven, De, Suvranu, Intes, Xavier

“… To the best of our knowledge, this is the first investigation to report on the use of a denoising autoencoder (DAE …”
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Combined Denoising and Suppression of Transient Artifacts in Arterial Spin Labeling MRI Using Deep Learning von Hales, Patrick W., Pfeuffer, Josef, Clark, Chris

“… Field Strength/Sequence 3T / pseudo‐continuous and pulsed ASL with 3D gradient‐and‐spin‐echo readout. Assessment A denoising autoencoder …”
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EEG Connectivity Analysis Using Denoising Autoencoders for the Detection of Dyslexia von Martinez-Murcia, Francisco J, Ortiz, Andres, Gorriz, Juan Manuel, Ramirez, Javier, Lopez-Abarejo, Pedro Javier, Lopez-Zamora, Miguel, Luque, Juan Luis

“… The Temporal Sampling Framework (TSF) theorizes that the characteristic phonological difficulties of dyslexia are caused by an atypical oscillatory sampling at …”
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Heart rate detection of ballistocardiogram based on improved DAE and template matching method von Mou, Zonglei, Han, Lei, Chen, Yu

“… ) and an improved Denoising Autoencoder (DAE), referred to as the GDAE model, to accurately detect heart rate in noise-contaminated signals …”
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Mood detection from daily conversational speech using denoising autoencoder and LSTM von Kun-Yi Huang, Chung-Hsien Wu, Ming-Hsiang Su, Hsiang-Chi Fu

“… Then, a denoising autoencoder (DAE) is used to construct an emotion conversion model to characterize the relationship between the perceived …”
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EEG Connectivity Analysis Using Denoising Autoencoders for the Detection of Dyslexia von Francisco Jesus Martinez-Murcia, Ortiz, Andrés, Górriz, Juan Manuel, Ramírez, Javier, Lopez-Perez, Pedro Javier, López-Zamora, Miguel, Luque, Juan Luis

“… The Temporal Sampling Framework (TSF) theorizes that the characteristic phonological difficulties of dyslexia are caused by an atypical oscillatory sampling at …”
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Denoising-Based Domain Adaptation Network for EEG Source Imaging von Li, Runze

“… However, it is still a major challenge to deal with the domain shift problem between the datasets of different subjects or sessions in ESI problem …”
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EMG Based Rehabilitation Gesture Recognition Using DAE-CNN-LSTM Hybrid Model von Cao, Wujing, Guo, Xinqiang, Zou, Yupeng, Zhang, Shuo, Luo, Mingxiang, Kobsiriphat, Worawarit, Wu, Xinyu, Yin, Meng

“… We adopt a strategy combining denoising autoencoder (DAE), convolutional neural network (CNN), and long short-term memory …”
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Denoising-based UNMT is more robust to word-order divergence than MASS-based UNMT von Banerjee, Tamali, Rudra Murthy V, Bhattacharyya, Pushpak

“… We aim to investigate whether UNMT approaches with self-supervised pre-training are robust to word-order divergence between language pairs. We achieve this by …”
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Hybrid deep learning framework for EMG signal-based recognition of rehabilitation gestures von Li, Jinke, Guo, Xinqiang, Luo, Mingxiang, Zou, Yupeng, Zhang, Shuo, Wu, Xinyu, Yin, Meng, Cao, Wujing

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Representative Random Sampling for Feature Engineering of -Omics Data: Using Machine Learning to Identify Biomarkers for Head and Neck Squamous Cell Carcinoma von Rendleman, Michael C

“… High-dimensional cancer data can be burdensome to analyze, with complex relationships between molecular measurements, clinical diagnostics, and treatment …”
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Improving The Robustness Of Right Whale Detection In Noisy Conditions Using Denoising Autoencoders And Augmented Training von Vickers, W., Milner, B., Lee, R.

“… The aim of this paper is to examine denoising autoencoders (DAEs) for improving the detection of right whales recorded in harsh marine environments …”
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