Výsledky vyhledávání - denoising autoencoder~

Automated feature learning for nonlinear process monitoring – An approach using stacked denoising autoencoder and k-nearest neighbor rule Autor Zhang, Zehan, Jiang, Teng, Li, Shuanghong, Yang, Yupu

“…•Automated feature learning based on stacked denoising autoencoder (SDAE) and k-nearest neighbor rule (kNN…”
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A correlative denoising autoencoder to model social influence for top- N recommender system Autor PAN, Yiteng, HE, Fazhi, YU, Haiping

“… Towards this problem, we propose a novel correlative denoising autoencoder (CoDAE) method by taking correlations between users with multiple roles into account…”
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Signal‐to‐noise ratio enhancement for Raman spectra based on optimized Raman spectrometer and convolutional denoising autoencoder Autor Fan, Xian‐guang, Zeng, Yingjie, Zhi, Yu‐Liang, Nie, Ting, Xu, Ying‐jie, Wang, Xin

“…‐the‐shelf cylindrical lens. On the other side of the algorithm, a relevant automatic denoising method of convolutional denoising autoencoder (CDAE…”
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Bidirectional Denoising Autoencoders Based Robust Representation Learning for Underwater Acoustic Target Signal Denoising Autor Dong, Yafen, Shen, Xiaohong, Wang, Haiyan

“… channels, which brings adverse effects to underwater acoustic target recognition. To improve the recognition accuracy of underwater targets under background noise interference, a bidirectional denoising autoencoder (BDAE…”
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Hyperspectral image classification using k-sparse denoising autoencoder and spectral–restricted spatial characteristics Autor Lan, Rushi, Li, Zeya, Liu, Zhenbing, Gu, Tianlong, Luo, Xiaonan

“… This paper proposes a novel k-sparse denoising autoencoder (KDAE) with a softmax classifier for HSI classification…”
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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 Autor 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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Within-project and cross-project just-in-time defect prediction based on denoising autoencoder and convolutional neural network Autor Zhu, Kun, Zhang, Nana, Ying, Shi, Zhu, Dandan

“… Therefore, the authors propose a novel just-in-time defect prediction model named DAECNN-JDP based on denoising autoencoder and convolutional neural network in this study, which has three main advantages…”
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Blind Denoising Autoencoder Autor Majumdar, Angshul

“… But there has been no autoencoder-based solution for the said blind denoising approach. So far, autoencoder-based denoising formulations have learned the model on a separate training data and have used the learned model to denoise test samples…”
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Multi-Type Missing Imputation of Time-Series Power Equipment Monitoring Data Based on Moving Average Filter–Asymmetric Denoising Autoencoder Autor Jiang, Ling, Gu, Juping, Zhang, Xinsong, Hua, Liang, Cai, Yueming

“… This leads to the poor quality and utilization difficulties of the collected data. To address this problem, this paper customizes methodology that combines an asymmetric denoising autoencoder (ADAE…”
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Batch process quality prediction based on denoising autoencoder-spatial temporal convolutional attention mechanism fusion network: Batch process quality prediction based on denoising autoencoder-spatial temporal convolutional attention mechanism fusion network Autor Zhang, Yan, Cao, Jie, Zhao, Xiaoqiang, Hui, Yongyong

“… to prediction performance. Therefore, a denoising autoencoder-Spatial Temporal Convolution Attention Fusion Network (DAE-STCAFN…”
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RunDAE model: Running denoising autoencoder models for denoising ECG signals Autor Samann, Fars, Schanze, Thomas

“…The denoising autoencoder (DAE) is commonly used to denoise bio-signals such as electrocardiogram (ECG…”
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Deep denoising autoencoder-assisted continuous scoring of peak quality in high-resolution LC−MS data Autor 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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DEVDAN: Deep evolving denoising autoencoder Autor Ashfahani, Andri, Pratama, Mahardhika, Lughofer, Edwin, Ong, Yew-Soon

“…The Denoising Autoencoder (DAE) enhances the flexibility of data stream method in exploiting unlabeled samples…”
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Stacked denoising autoencoder based fault location in voltage source converters‐high voltage direct current Autor Luo, Guomin, Cheng, Mengxiao, Hei, Jiaxin, Wang, Xiaojun, Huang, Weibo, He, Jinghan

“… A stacked denoising autoencoder based fault location method for high voltage direct current transmission systems is proposed…”
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MDGN: Circuit design of memristor‐based denoising autoencoder and gated recurrent unit network for lithium‐ion battery state of charge estimation Autor Wang, Jiayang, Zhang, Xinghao, Han, Yifeng, Lai, Chun Sing, Dong, Zhekang, Ma, Guojin, Gao, Mingyu

“…‐based denoising autoencoder and gated recurrent unit network (MDGN) for fast and accurate SOC estimation of lithium‐ion batteries…”
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Deep learning for electrolysis process anode effect prediction based on long short-term memory network and stacked denoising autoencoder Autor Yin, Gang, Li, Yi-Hui, Yan, Fei-Ya, Quan, Peng-Cheng, Wang, Min, Cao, Wen-Qi, Xu, Heng-Quan, Lu, Jian, He, Wen

“… A stacked denoising autoencoder is utilized to denoise and extract features from a large number of long-period parameter data…”
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Knock-Knock: Acoustic object recognition by using stacked denoising autoencoders Autor Luo, Shan, Zhu, Leqi, Althoefer, Kaspar, Liu, Hongbin

“… In this paper, stacked denoising autoencoders are applied to train a deep learning model. Knocking each object in our test set 120 times with a marker pen to obtain…”
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Remaining-capacity estimation of lithium-ion batteries using heatmap-based denoising autoencoder and vision transformer algorithm Autor Jang, Yunseo, Park, Joung-Hu

“… We propose a deep learning framework that transforms multichannel time-series measurements into correlation heatmaps, which are then fed into a denoising autoencoder (DAE…”
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Attention-Based Convolutional Denoising Autoencoder for Two-Lead ECG Denoising and Arrhythmia Classification Autor Singh, Prateek, Sharma, Ambalika

“… To achieve this, a novel attention-based convolutional denoising autoencoder (ACDAE) model is proposed that utilizes a skip-layer and attention module for reliable reconstruction of ECG signals from extreme noise conditions…”
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A Denoising Autoencoder-Based Bearing Fault Diagnosis System for Time-Domain Vibration Signals Autor Gu, Yi, Cao, Jiawei, Song, Xin, Yao, Jian

“… To effectively detect, locate, and identify faults in rolling bearings, a stacked noise reduction autoencoder is utilized for abstracting characteristic from the original vibration of signals…”
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