Search Results - "stacked denoising autoencoder"

Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification by Lu, Chen, Wang, Zhen-Ya, Qin, Wei-Li, Ma, Jian

“…Effective fault diagnosis has long been a research topic in the prognosis and health management of rotary machinery engineered systems due to the benefits such…”
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Improved deep reinforcement learning for car-following decision-making by Yang, Xiaoxue, Zou, Yajie, Zhang, Hao, Qu, Xiaobo, Chen, Lei

“…Accuracy improvement of Car-following (CF) model has attracted much attention in recent years. Although a few studies incorporate deep reinforcement learning…”
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Background Prior-Based Salient Object Detection via Deep Reconstruction Residual by Junwei Han, Dingwen Zhang, Xintao Hu, Lei Guo, Jinchang Ren, Feng Wu

“…Detection of salient objects from images is gaining increasing research interest in recent years as it can substantially facilitate a wide range of…”
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A deep learning method for predicting lead content in oilseed rape leaves using fluorescence hyperspectral imaging by Zhou, Xin, Zhao, Chunjiang, Sun, Jun, Cao, Yan, Yao, Kunshan, Xu, Min

“…•FHSI was applied to the detection of lead content in oilseed rape leaves.•WT-SDAE model was proposed for deep feature extraction.•The WT-SDAE-SVR model…”
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Life prediction of lithium-ion batteries based on stacked denoising autoencoders by Xu, Fan, Yang, Fangfang, Fei, Zicheng, Huang, Zhelin, Tsui, Kwok-Leung

“…•Introduce the CFS clustering model for feature selection.•Using the SDAE for life prediction at early life stage.•Extracting the original features using…”
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Transfer learning for short-term wind speed prediction with deep neural networks by Hu, Qinghua, Zhang, Rujia, Zhou, Yucan

“…As a type of clean and renewable energy source, wind power is widely used. However, owing to the uncertainty of wind speed, it is essential to build an…”
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Deep Neural Networks for wireless localization in indoor and outdoor environments by Zhang, Wei, Liu, Kan, Zhang, Weidong, Zhang, Youmei, Gu, Jason

“…In this paper, we propose a wireless positioning method based on Deep Learning. To deal with the variant and unpredictable wireless signals, the positioning is…”
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Multimode process monitoring based on hierarchical mode identification and stacked denoising autoencoder by Gao, Huihui, Wei, Chen, Huang, Wenjie, Gao, Xuejin

“…•A novel hierarchical mode identification strategy is proposed for multimode process.•An improved density peaks clustering algorithm called LDRSDPC is…”
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Two-Stream Deep Architecture for Hyperspectral Image Classification by Hao, Siyuan, Wang, Wei, Ye, Yuanxin, Nie, Tingyuan, Bruzzone, Lorenzo

“…Most traditional approaches classify hyperspectral image (HSI) pixels relying only on the spectral values of the input channels. However, the spatial context…”
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Automated feature learning for nonlinear process monitoring – An approach using stacked denoising autoencoder and k-nearest neighbor rule by Zhang, Zehan, Jiang, Teng, Li, Shuanghong, Yang, Yupu

“…•Automated feature learning based on stacked denoising autoencoder (SDAE) and k-nearest neighbor rule (kNN) for nonlinear process monitoring.•SDAE is used to…”
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A deep learning ensemble approach for crude oil price forecasting by Zhao, Yang, Li, Jianping, Yu, Lean

“…As crude oil price is influenced by numerous factors, capturing its behavior precisely is quite challenging, and thus leads to the difficulty of forecasting…”
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A sparse stacked denoising autoencoder with optimized transfer learning applied to the fault diagnosis of rolling bearings by Sun, Meidi, Wang, Hui, Liu, Ping, Huang, Shoudao, Fan, Peng

“…•Fault diagnosis by stacked autoencoder requires less professional knowledge.•Domain adaptation by optimized transfer learning reduces the algorithm’s…”
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Change detection based on deep feature representation and mapping transformation for multi-spatial-resolution remote sensing images by Zhang, Puzhao, Gong, Maoguo, Su, Linzhi, Liu, Jia, Li, Zhizhou

“…Multi-spatial-resolution change detection is a newly proposed issue and it is of great significance in remote sensing, environmental and land use monitoring,…”
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Deep learning framework designed for high-performance lithium-ion batteries state monitoring by Takyi-Aninakwa, Paul, Wang, Shunli, Liu, Guangchen, Fernandez, Carlos, Kang, Wenbin, Song, Yingze

“…Accurate state of charge (SOC) estimation is crucial for ensuring the safety of batteries, especially in real-time battery management system (BMS)…”
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AIMAFE: Autism spectrum disorder identification with multi-atlas deep feature representation and ensemble learning by Wang, Yufei, Wang, Jianxin, Wu, Fang-Xiang, Hayrat, Rahmatjan, Liu, Jin

“…•Multi-atlas functional connectivity is calculated as the original feature representation.•Multi-atlas deep feature representation is extracted by a deep…”
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A New Online Detection Approach for Rolling Bearing Incipient Fault via Self-Adaptive Deep Feature Matching by Mao, Wentao, Chen, Jiaxian, Liang, Xihui, Zhang, Xinming

“…This paper presents a new online detection approach for rolling bearing's incipient fault based on self-adaptive deep feature matching (SDFM). This approach…”
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Adaptive Diagnosis for Transformer with Unknown Faults Based on Antenna-Augmented RFID Sensor and Deep Learning by Wang, Tao, Xiao, Yanxia, Li, Bing, He, Yigang

“…In engineering practice, transformers always have one or more new mechanical fault types that have not been found yet, which would decrease the diagnosis…”
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A DEEP LEARNING APPROACH FOR CANCER DETECTION AND RELEVANT GENE IDENTIFICATION by DANAEE, PADIDEH, GHAEINI, REZA, HENDRIX, DAVID A.

“…Cancer detection from gene expression data continues to pose a challenge due to the high dimensionality and complexity of these data. After decades of research…”
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Cosaliency Detection Based on Intrasaliency Prior Transfer and Deep Intersaliency Mining by Zhang, Dingwen, Han, Junwei, Han, Jungong, Shao, Ling

“…As an interesting and emerging topic, cosaliency detection aims at simultaneously extracting common salient objects in multiple related images. It differs from…”
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A deep autoencoder feature learning method for process pattern recognition by Yu, Jianbo, Zheng, Xiaoyun, Wang, Shijin

“…Schematic diagram of the SDAE-based process pattern detection and recognition. [Display omitted] •A stacked denoising autoencoder (SDAE)-based model is…”
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