Search Results - Deep denoising autoencoder

Deep denoising autoencoder-assisted continuous scoring of peak quality in high-resolution LC−MS data by Ji, Hongchao, Tian, Jing

“… Here we put forward AutoMS, which employs a deep learning-based denoising autoencoder to grasp the common characteristics of chromatographic peaks, and predict noise-deducted peaks from the original peak profiles…”
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Predicting protein–protein interactions in microbes associated with cardiovascular diseases using deep denoising autoencoders and evolutionary information by Zhou, Senyu, Luo, Jian, Tang, Mei, Li, Chaojun, Li, Yang, He, Wenhua

“… In this study, we present a novel model, the deep denoising autoencoder for protein-protein interaction (DAEPPI…”
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Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label by Xu, Fan, Tse, Wai tai Peter, Tse, Yiu Lun

“…Most deep learning models such as stacked autoencoder (SAE) and stacked denoising autoencoder (SDAE…”
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DEVDAN: Deep evolving denoising autoencoder by Ashfahani, Andri, Pratama, Mahardhika, Lughofer, Edwin, Ong, Yew-Soon

“… Deep evolving denoising autoencoder (DEVDAN), is proposed in this paper. It features an open structure in the generative phase and the discriminative phase where the hidden units can be automatically added and discarded on the fly…”
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Whispered speech recognition using deep denoising autoencoder by Grozdić, Đorđe T., Jovičić, Slobodan T., Subotić, Miško

“…Recently Deep Denoising Autoencoders (DDAE) have shown state-of-the-art performance on various machine learning tasks…”
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A Deep Denoising Autoencoder Approach to Improving the Intelligibility of Vocoded Speech in Cochlear Implant Simulation by Lai, Ying-Hui, Chen, Fei, Wang, Syu-Siang, Lu, Xugang, Tsao, Yu, Lee, Chin-Hui

“… Identifying an effective NR approach has long been a key topic in CI research. Method: Recently, a deep denoising autoencoder (DDAE…”
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Convolutional deep denoising autoencoders for radio astronomical images by Gheller, C, Vazza, F

“…ABSTRACT We apply a Machine Learning technique known as Convolutional Denoising Autoencoder to denoise synthetic images of state-of-the-art radio telescopes, with the goal of detecting the faint…”
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Bone-conducted speech enhancement using deep denoising autoencoder by Liu, Hung-Ping, Tsao, Yu, Fuh, Chiou-Shann

“…Bone-conduction microphones (BCMs) capture speech signals based on the vibrations of the speaker's skull and exhibit better noise-resistance capabilities than…”
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A Pythagorean-Type Fuzzy Deep Denoising Autoencoder for Industrial Accident Early Warning by Zheng, Yu-Jun, Chen, Sheng-Yong, Xue, Yu, Xue, Jin-Yun

“… This paper presents a fuzzy deep neural network for early warning of industrial accidents, which equips the classical deep denoising autoencoder (DDAE…”
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Enhancing Sound-Based Anomaly Detection Using Deep Denoising Autoencoder by Kim, Seong-Mok, Soo Kim, Yong

“… This study proposes a method that uses a deep denoising autoencoder to filter out various levels of industrial noise from audio data and employs unsupervised learning models for rapid and accurate anomaly detection…”
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Dynamic dispatching system using a deep denoising autoencoder for semiconductor manufacturing by Lee, Sangmin, Kim, Hae Joong, Kim, Seoung Bum

“…Deep denoising autoencoders (DDAE), which are variants of the autoencoder, have shown outstanding performance in various machine learning tasks…”
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Whispered Speech Recognition Using Deep Denoising Autoencoder and Inverse Filtering by Grozdic, Dorde T., Jovicic, Slobodan T.

“…, addresses the problems of whispered speech recognition in mismatched conditions, and then proposes a new robust cepstral features and preprocessing approach based on deep denoising autoencoder (DDAE…”
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Random noise attenuation of ocean bottom seismometers based on a substep deep denoising autoencoder by Lin, Haoran, Xu, Jian, Xing, Lei, Li, Qianqian, Liu, Huaishan

“…‐layer denoising autoencoder. We input the t−x$t-x$ domain data into the denoising autoencoder, the encoder compresses the signal and noise and extracts the main…”
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A novel unsupervised approach based on the hidden features of Deep Denoising Autoencoders for COVID-19 disease detection by Scarpiniti, Michele, Sarv Ahrabi, Sima, Baccarelli, Enzo, Piazzo, Lorenzo, Momenzadeh, Alireza

“…Chest imaging can represent a powerful tool for detecting the Coronavirus disease 2019 (COVID-19). Among the available technologies, the chest Computed…”
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DDANF: Deep denoising autoencoder normalizing flow for unsupervised multivariate time series anomaly detection by Zhao, Xigang, Liu, Peng, Mahmoudi, Saïd, Garg, Sahil, Kaddoum, Georges, Hassan, Mohammad Mehedi

“…In recent years, the proliferation of IoT technologies and the widespread adoption of wireless sensors across various critical infrastructures such as power…”
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Separating the EoR signal with a convolutional denoising autoencoder: a deep-learning-based method by Li, Weitian, Xu, Haiguang, Ma, Zhixian, Zhu, Ruimin, Hu, Dan, Zhu, Zhenghao, Gu, Junhua, Shan, Chenxi, Zhu, Jie, Wu, Xiang-Ping

“… of interferometers, will generate significant fluctuations along the frequency dimension. To address this issue, we propose a novel deep-learning-based method that uses a nine-layer convolutional denoising autoencoder (CDAE…”
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Single-cell RNA-seq denoising using a deep count autoencoder by Eraslan, Gökcen, Simon, Lukas M., Mircea, Maria, Mueller, Nikola S., Theis, Fabian J.

“… We propose a deep count autoencoder network (DCA) to denoise scRNA-seq datasets. DCA takes the count distribution, overdispersion and sparsity of the data into account…”
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Environmental Noise Reduction based on Deep Denoising Autoencoder by Azmat, A., Ali, I., Ariyanti, W., Putra, M. G. L., Nadeem, T.

“… To cope with this challenge, an explicit denoising framework called Deep Denoising Autoencoder (DDAE…”
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Stealthy data integrity attack identification in smart grid networks utilizing deep denoising autoencoder by Kousar, Anila, Ahmed, Saeed, Altamimi, Abdullah, Kim, Su Min, Khan, Zafar A.

“… To this end, this paper proposes a deep denoising autoencoder (DAE)-based framework for dimensionality…”
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Deep Architecture for High-Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning by Kang, Gaoqiang, Gao, Shibin, Yu, Long, Zhang, Dongkai

“… To overcome these problems, this paper proposes a novel insulator surface defect detection system using a deep convolutional neural network (CNN…”
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