Suchergebnisse - hierarchical denoising autoencoder

Target Detection With Unconstrained Linear Mixture Model and Hierarchical Denoising Autoencoder in Hyperspectral Imagery von Li, Yunsong, Shi, Yanzi, Wang, Keyan, Xi, Bobo, Li, Jiaojiao, Gamba, Paolo

“… mixture model and deep learning. Our proposed detector firstly reduces interference via a specifically designed deep-learning-based hierarchical denoising autoencoder, and then carries out accurate detection with a two-step subspace …”
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IMATAC imputes single-cell ATAC-seq data by deep hierarchical network with denoising autoencoder von Li, Yao, Lyu, Hongqiang, Li, Kexin, Liu, Yuan, Zhang, Xinman, Liu, Ze, Jing, Pengcheng, Han, Peng

“… Herein, we propose IMATAC, a deep hierarchical network with denoising autoencoder for imputing scATAC-seq data in the form of peak by cell …”
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Convolutional adaptive denoising autoencoders for hierarchical feature extraction von ZHANG, Qianjun, ZHANG, Lei

“… Convolutional neural networks (CNNs) are typical structures for deep learning and are widely used in image recognition and classification. However, the random …”
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Multimode process monitoring based on hierarchical mode identification and stacked denoising autoencoder von Gao, Huihui, Wei, Chen, Huang, Wenjie, Gao, Xuejin

“… •A novel hierarchical mode identification strategy is proposed for multimode process …”
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Multiscale intelligent fault detection system based on agglomerative hierarchical clustering using stacked denoising autoencoder with temporal information von Yu, Jianbo, Yan, Xuefeng

“… In this study, the interpretability and suitability of stacked denoising autoencoder (SDAE) in process monitoring territory are theoretically analyzed and validated …”
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Hyperspectral Target Detection with Hierarchical Denoising Autoencoder and Subspace Projection von Shi, Yanzi, Wang, Keyan, Li, Jiaojiao, Li, Yunsong

“… First, a hierarchical denoising autoencoder (HDAE) is specifically designed for redundant interference removal …”
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An adaptive hierarchical hybrid kernel ELM optimized by aquila optimizer algorithm for bearing fault diagnosis von Yan, Hao, Shang, Liangliang, Chen, Wan, Jiang, Mengyao, lu, Tianqi, Li, Fei

“… This paper proposes an intelligent bearing fault diagnosis method that improves classification accuracy using a stacked denoising autoencoder (SDAE …”
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Recognition of online handwritten Bangla characters using hierarchical system with Denoising Autoencoders von Pal, Arghya, Pawar, J. D.

“… This work describes the recognition of online handwritten Bengali characters using Deep Denoising Autoencoder with Multilayer Perceptron (MLP …”
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Growing Hierarchical Self-Organising Representation Map (GHSORM) von Coulson, Matthew, Ferles, Christos, Winberg, Simon, Naidoo, Kevin J.

“… The Growing Hierarchical Self-Organising Representation Map (GHSORM) is a model fusing the denoising autoencoder, used to better represent a dataset …”
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Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction von Shi, Yifei, Chang, Angel X., Wu, Zhelun, Savva, Manolis, Xu, Kai

“… We present a variational denoising recursive autoencoder (VDRAE) that generates and iteratively refines a hierarchical representation of 3D object layouts, interleaving bottom-up encoding for context aggregation and top-down decoding for propagation …”
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Abnormality Monitoring in the Blast Furnace Ironmaking Process Based on Stacked Dynamic Target-Driven Denoising Autoencoders von Jiang, Ke, Jiang, Zhaohui, Xie, Yongfang, Pan, Dong, Gui, Weihua

“… Thus, this article proposes a novel stacked dynamic target-driven denoising autoencoder for layer-by-layer hierarchical feature representation, and the dynamic relationship between samples …”
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Stacked Graph Fusion Denoising Autoencoder for Hyperspectral Anomaly Detection von Zhang, Yongshan, Li, Yijiang, Wang, Xinxin, Jiang, Xinwei, Zhou, Yicong

“… With the designed graph fusion strategy, an advanced graph denoising autoencoder with deep architecture is developed in a hierarchical manner …”
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State Assessment and Fault Prediction Method of Distribution Terminal Based on SDAE and Hierarchical Bayesian von Liu, Runmiao, Feng, Shiyong, Cai, Yueming, Liu, Mingxiang

“… A reliability assessment and prediction model based on stacked denoising autoencoder and hierarchical bayesian is proposed in this paper …”
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Stacked Denoising Variational Auto Encoder Model for Extractive Web Text Summarization von Yadav, Madhuri, Katarya, Rahul

“… Extracting and concatenating distilled content from a corpus into a summary is a technique known as extractive summarization. In recent days, extractive …”
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Deep learning-assisted analysis of automobiles handling performances von Sapienza, Davide, Paganelli, Davide, Prato, Marco, Bertogna, Marko, Spallanzani, Matteo

“… A categorical variable quantifies the evaluations of handling properties. We describe an original deep learning system, featuring a denoising autoencoder and hierarchical attention mechanisms, that we designed …”
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Fault Diagnosis for Hydraulic Servo System: A Stacked Denoising Autoencoder Method based on Self-Learning of Robustness Features von Wang, Zhenya, Fan, Jiaxuan, Huang, Hu, Han, Te

“… The fault diagnosis of hydraulic servo system attracts more attention in complex system prognostics and health management. As the precondition of most fault …”
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Robust Feature Extraction for Geochemical Anomaly Recognition Using a Stacked Convolutional Denoising Autoencoder von Xiong, Yihui, Zuo, Renguang

“… Our approach adopted a stacked convolutional denoising autoencoder (SCDAE) to extract robust features and decreased the level of sensitivity to partially corrupted data, that is, input data that are partially missing …”
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Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification von Lu, Chen, Wang, Zhen-Ya, Qin, Wei-Li, Ma, Jian

“… improvements, and economical efficiency. This paper investigates an effective and reliable deep learning method known as stacked denoising autoencoder (SDA …”
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Improving transfer learning accuracy by reusing Stacked Denoising Autoencoders von Kandaswamy, Chetak, Silva, Luis M., Alexandre, Luis A., Sousa, Ricardo, Santos, Jorge M., de Sa, Joaquim Marques

“… A Stacked Denoising Autoencoder (SDA) is a deep model able to represent the hierarchical features needed for solving classification problems …”
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Multi-Omics Data Integration for Improved Cancer Subtyping via Denoising Autoencoder-Based Multi-Kernel Learning von Yao, Xiukun, Wang, Tong, Yang, Qi, Wang, Jiawen, Qi, Yao, Xu, Tong, Wei, Zhiwen, Cui, Yuehua, Cao, Hongyan, Yun, Keming

“… : Considering the high-dimensional nature inherent to various multi-omics data types, we introduce an innovative deep learning framework, DAE-MKL, which integrates denoising autoencoders with multi …”
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