Search Results - Elastic Stacked Denoising Autoencoder

Intelligent Detection of Railway Axles Fatigue Crack Using Acoustic Emission-Stacked Denoising Autoencoders.

Authors: Lin, Li Zhao, Shuang Tang, Xiaowen et al.

Source: Journal of Nondestructive Evaluation; Dec2025, Vol. 44 Issue 4, p1-22, 22p

Subject Terms: FATIGUE cracks, ACOUSTIC emission, DEEP learning, NONDESTRUCTIVE testing, DETECTION algorithms, FEATURE extraction, AXLES

Elastic SDAE: An Adaptive Noise Selection for Stacked Denoising Auto encoder

Authors: Usha Devi G Gokulnath Bv

Source: 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE). :1-5

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: http://xplorestaging.ieee.org/ielx7/9070069/9077582/09077788.pdf?arnumber=9077788
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=9077788

Multi-lingual handwriting recovery framework based on convolutional denoising autoencoder with attention model.

Authors: Rabhi, Besma Elbaati, Abdelkarim Boubaker, Houcine et al.

Source: Multimedia Tools & Applications; Mar2024, Vol. 83 Issue 8, p22295-22326, 32p

FAULT DIAGNOSIS ALGORITHM OF ELECTRIC VEHICLE GEARBOX BASED ON SDEA-BI GRU.

Authors: Linlin ZHAO Tao WU

Source: Diagnostyka; 2024, Vol. 25 Issue 2, p1-9, 9p

Subject Terms: FAULT diagnosis, ELECTRIC vehicles, ELECTRIC faults, HYBRID electric vehicles, FEATURE extraction, GEARBOXES

Deep learning in vision-based static hand gesture recognition.

Authors: Oyedotun, Oyebade Khashman, Adnan

Source: Neural Computing & Applications; Dec2017, Vol. 28 Issue 12, p3941-3951, 11p

Subject Terms: ARTIFICIAL neural networks, PATTERN perception, GESTURE, NEURAL circuitry, MACHINE learning, NEURAL computers, DEEP learning, SUPPORT vector machines

Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images.

Authors: Chen, Sihong Qin, Jing Ji, Xing et al.

Source: IEEE Transactions on Medical Imaging; Mar2017, Vol. 36 Issue 3, p802-814, 13p

Subject Terms: PULMONARY nodules, COMPUTED tomography, DEEP learning, SEARCH engines, RADIOLOGISTS

Reducing false damage detections in guided ultrasonic wave monitoring systems using a denoising autoencoder.

Authors: Kong Chen, Yon Bakhary, Norhisham Padil, Khairul Hazman et al.

Source: Nondestructive Testing & Evaluation; Apr2025, Vol. 40 Issue 4, p1610-1640, 31p

Subject Terms: STRUCTURAL health monitoring, NUCLEAR industry, ULTRASONIC waves, AUTOENCODERS, TEMPERATURE effect

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: Y. Zhang et al.

Authors: Zhang, Yan Cao, Jie Zhao, Xiaoqiang et al.

Source: Applied Intelligence; Apr2025, Vol. 55 Issue 6, p1-20, 20p

Machine learning in subsurface physical properties and lithofacies prediction in a mining context.

Authors: Balaguera A Torné M Carbonell R et al.

Source: Scientific reports [Sci Rep] 2025 Jul 21; Vol. 15 (1), pp. 26495. Date of Electronic Publication: 2025 Jul 21.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: PubMed not MEDLINE; MEDLINE

A New Training Principle for Stacked Denoising Autoencoders.

Authors: You, Qianhaozhe Zhang, Yu-Jin

Source: 2013 Seventh International Conference on Image & Graphics; 2013, p384-389, 6p

Ultrasonic guided Wave Signal Denoising Method Based on one-dimensional convolution and Full connection Model Fusion Denoising autoencoder.

Authors: Yang, Yingfeng Qiu, Guangwen Lin, Yizhou et al.

Source: Journal of Physics: Conference Series; 2024, Vol. 2822 Issue 1, p1-12, 12p

Distributed Robust Process Monitoring Based on Optimized Denoising Autoencoder With Reinforcement Learning.

Authors: Chen, Shutian Jiang, Qingchao

Source: IEEE Transactions on Instrumentation & Measurement; 2022, Vol. 71, p1-11, 11p

Subject Terms: DISTRIBUTED computing, CHEMICAL processes, FEATURE extraction, NOISE control, COMPUTER simulation, REINFORCEMENT learning, IMAGE denoising

Deep Learning Algorithms for Human Activity Recognition in Manual Material Handling Tasks.

Authors: Bassani, Giulia Avizzano, Carlo Alberto Filippeschi, Alessandro

Source: Sensors (14248220); Nov2025, Vol. 25 Issue 21, p6705, 20p

Subject Terms: HUMAN activity recognition, MATERIALS handling, CONVOLUTIONAL neural networks, DEEP learning, RECOGNITION (Psychology), WEARABLE technology, INDUSTRIAL safety, LONG short-term memory

Self-Supervised Autoencoders for Visual Anomaly Detection.

Authors: Bauer, Alexander Nakajima, Shinichi Müller, Klaus-Robert

Source: Mathematics (2227-7390); Dec2024, Vol. 12 Issue 24, p3988, 40p

Subject Terms: ORTHOGRAPHIC projection, AUTOENCODERS, DATA distribution, NOISE, ARGUMENT

Static hand gesture recognition using stacked Denoising Sparse Autoencoders.

Authors: Kumar, Varun Nandi, G.C. Kala, Rahul

Source: 2014 Seventh International Conference on Contemporary Computing (IC3); 2014, p99-104, 6p

Data-Driven Method for Real-Time Reconstruction of the Structural Displacement Field.

Authors: Yan, Jun Du, Hongze Bu, Yufeng et al.

Source: Journal of Aerospace Engineering; May2024, Vol. 37 Issue 3, p1-11, 11p

Subject Terms: CONVOLUTIONAL neural networks, DEEP learning, KALMAN filtering

Denoising ambient seismic field correlation functions with convolutional autoencoders.

Authors: Viens, Loïc Van Houtte, Chris

Source: Geophysical Journal International; Mar2020, Vol. 220 Issue 3, p1521-1535, 15p

Subject Terms: SURFACE waves (Seismic waves), SEISMIC wave velocity, SURFACE of the earth, RELATIVE velocity, AUTOMORPHISMS, PROPORTIONAL hazards models, METROPOLITAN areas

Geographic Terms: JAPAN

A model fusion optimization strategy for lithium mill equipment state prediction.

Authors: Xiao, Yanjun Ning, Fuan Yin, Shanshan et al.

Source: Measurement Science & Technology; Dec2024, Vol. 35 Issue 12, p1-24, 24p

Unsupervised environmental operating condition compensation strategies in a guided ultrasonic wave monitoring system: evaluation and comparison.

Authors: Yon, Kong Chen Bakhary, Norhisham Padil, Khairul Hazman et al.

Source: Journal of Civil Structural Health Monitoring; Apr2024, Vol. 14 Issue 4, p861-884, 24p

Optimized Machine Learning-Based Intrusion Detection System for Fog and Edge Computing Environment.

Authors: Alzubi, Omar A. Alzubi, Jafar A. Alazab, Moutaz et al.

Source: Electronics (2079-9292); Oct2022, Vol. 11 Issue 19, p3007, 16p

Subject Terms: INTRUSION detection systems (Computer security), EDGE computing, PARTICLE swarm optimization, SUBSET selection, ELECTRONIC data processing, CLOUD computing