Search Results - "Deep Autoencoder"

Fast deep autoencoder for federated learning by Novoa-Paradela, David, Fontenla-Romero, Oscar, Guijarro-Berdiñas, Bertha

“…•A fast and privacy-preserving training algorithm for deep autoencoders is proposed.•The encoder block of the autoencoder is trained using Singular Value…”
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Unsupervised detection of multivariate geochemical anomalies using a high-performance deep autoencoder Gaussian mixture model by Wang, Xuemei, Chen, Yongliang

“…It is of great significance to construct an efficient geochemical anomaly detection model for the successful accomplishment of a mineral exploration process in…”
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Ensemble unsupervised autoencoders and Gaussian mixture model for cyberattack detection by An, Peng, Wang, Zhiyuan, Zhang, Chunjiong

“…Previous studies have adopted unsupervised machine learning with dimension reduction functions for cyberattack detection, which are limited to performing…”
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A novel deep autoencoder feature learning method for rotating machinery fault diagnosis by Shao, Haidong, Jiang, Hongkai, Zhao, Huiwei, Wang, Fuan

“…[Display omitted] •A deep autoencoder feature learning method is proposed.•Maximum correntropy is used to design the new deep autoencoder loss…”
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Modified Deep Autoencoder Driven by Multisource Parameters for Fault Transfer Prognosis of Aeroengine by He, Zhiyi, Shao, Haidong, Ding, Ziyang, Jiang, Hongkai, Cheng, Junsheng

“…The existing fault prognosis techniques of aeroengine mostly focus on a single monitoring parameter under stable condition, and have low adaptability to new…”
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Multi-path long-term vessel trajectories forecasting with probabilistic feature fusion for problem shifting by Spadon, Gabriel, Kumar, Jay, Eden, Derek, van Berkel, Josh, Foster, Tom, Soares, Amilcar, Fablet, Ronan, Matwin, Stan, Pelot, Ronald

“…This paper presents a deep auto-encoder model and a phased framework approach to predict the next 12 h of vessel trajectories using 1 to 3 h of Automatic…”
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Developing deep learning based regression approaches for determination of chemical compositions in dry black goji berries (Lycium ruthenicum Murr.) using near-infrared hyperspectral imaging by Zhang, Chu, Wu, Wenyan, Zhou, Lei, Cheng, Huan, Ye, Xingqian, He, Yong

“…•Black goji berries total anthocyanins, flavonoids and phenolics were predicted by HSI.•SPA, CARS and PCA, WT were compared to obtain conventional features for…”
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DAEN: Deep Autoencoder Networks for Hyperspectral Unmixing by Su, Yuanchao, Li, Jun, Plaza, Antonio, Marinoni, Andrea, Gamba, Paolo, Chakravortty, Somdatta

“…Spectral unmixing is a technique for remotely sensed image interpretation that expresses each (possibly mixed) pixel as a combination of pure spectral…”
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Comparing Recognition Performance and Robustness of Multimodal Deep Learning Models for Multimodal Emotion Recognition by Liu, Wei, Qiu, Jie-Lin, Zheng, Wei-Long, Lu, Bao-Liang

“…Multimodal signals are powerful for emotion recognition since they can represent emotions comprehensively. In this article, we compare the recognition…”
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Health indicator for machine condition monitoring built in the latent space of a deep autoencoder by González-Muñiz, Ana, Díaz, Ignacio, Cuadrado, Abel A., García-Pérez, Diego

“…The construction of effective health indicators plays a key role in the engineering systems field: they reflect the degradation degree of the system under…”
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Prediction of multiple fatigue crack growth based on modified Paris model with particle filtering framework by Wang, Li, Zhang, Chao, Tao, Chongcong, Ji, Hongli, Yang, Yu, Qiu, Jinhao

“…This paper presents a novel method based on modified Paris model with particle filtering (PF) framework to prognosis fatigue multi-cracks in metal structures…”
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Applications of Deep Learning and Reinforcement Learning to Biological Data by Mahmud, Mufti, Kaiser, Mohammed Shamim, Hussain, Amir, Vassanelli, Stefano

“…Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various…”
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Brain tumor classification using a hybrid deep autoencoder with Bayesian fuzzy clustering-based segmentation approach by Siva Raja, P.M., rani, Antony Viswasa

“…In medical image processing, brain tumor detection and segmentation is a challenging and time-consuming task. Magnetic Resonance Image (MRI) scan analysis is a…”
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SWDAE: A New Degradation State Evaluation Method for Metro Wheels with Interpretable Health Indicator Construction based on Unsupervised Deep Learning by Mao, Wentao, Wang, Yu, Feng, Ke, Kou, Linlin, Zhang, Yanna

“…Machine learning has shown advantages in assessing wheel degradation in metro vehicles for fault prognostic and health management (PHM). However, practical…”
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Elastic deep autoencoder for text embedding clustering by an improved graph regularization by Daneshfar, Fatemeh, Soleymanbaigi, Sayvan, Nafisi, Ali, Yamini, Pedram

“…Text clustering is a task for grouping extracted information of the text in different clusters, which has many applications in recommender systems, sentiment…”
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Action recognition using optimized deep autoencoder and CNN for surveillance data streams of non-stationary environments by Ullah, Amin, Muhammad, Khan, Haq, Ijaz Ul, Baik, Sung Wook

“…Action recognition is a challenging research area in which several convolutional neural networks (CNN) based action recognition methods are recently presented…”
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Dynamic Low-Rank and Sparse Priors Constrained Deep Autoencoders for Hyperspectral Anomaly Detection by Lin, Sheng, Zhang, Min, Cheng, Xi, Shi, Lei, Gamba, Paolo, Wang, Hai

“…Linear-based low-rank and sparse models (LRSM) and nonlinear-based deep autoencoder (DAE) models have been proven to be effective for the task of anomaly…”
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Image encryption based on logistic chaotic systems and deep autoencoder by Sang, Yongpeng, Sang, Jun, Alam, Mohammad S.

“…•Deep autoencoder is incorporated with logistic chaotic systems for image encryption.•A single network can be utilized to encrypt different plaintext…”
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Inferring normality from noised samples: Enhanced deep autoencoder with image denoising for anomaly detection by Liang, Dong, Gao, Xinbo, Lu, Wen, Li, Jie

“…The goal of image anomaly detection is to detect and localize the patterns that do not meet the normal expectations in an image. The widely used…”
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A novel hybrid machine learning model for rapid assessment of wave and storm surge responses over an extended coastal region by Saviz Naeini, Saeed, Snaiki, Reda

“…Storm surge and waves are responsible for a substantial portion of tropical and extratropical cyclones-related damages. While high-fidelity numerical models…”
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