Search Results - Multi-scale sparse autoencoder

PolSAR image classification based on multi-scale stacked sparse autoencoder

Authors: Lu Zhang Licheng Jiao Wenping Ma et al.

Source: Neurocomputing. 351:167-179

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://www.sciencedirect.com/science/article/pii/S0925231219303649
https://dblp.uni-trier.de/db/journals/ijon/ijon351.html#ZhangJMDZ19
http://www.sciencedirect.com/science/article/pii/S0925231219303649

An industrial process monitoring method based on fusion of multi-scale sparse autoencoder and dual-branch slow feature architecture.

Authors: Ling, Guobi Wang, Zhiwen Wang, Jieying et al.

Source: Chemical Engineering Science. Feb2026:Part C, Vol. 321, pN.PAG-N.PAG. 1p.

Subject Terms: *FAULT diagnosis, *PROCESS optimization, *STATISTICAL correlation, *ARTIFICIAL neural networks, *MANUFACTURING process management

ESAE-SDA: ensemble sparse autoencoder framework for epigenomics-informed snoRNA-disease associations prediction.

Authors: Jiang, Xinqing Chen, Xiaojun Xu, Lifeng et al.

Source: BMC Bioinformatics; 10/31/2025, Vol. 26 Issue 1, p1-18, 18p

Subject Terms: EPIGENOMICS, NON-coding RNA, GENE expression, ARTIFICIAL intelligence, ENSEMBLE learning, AUTOENCODERS, DISEASE complications

Enhancing the robustness of the 1-D CNN model through NIRS data augmentation based on sparse autoencoder and CARS feature selection for mango DMC determination.

Authors: Yang, Dongfeng Hu, Jun

Source: Journal of Food Composition & Analysis. Dec2025:Part 3, Vol. 148, pN.PAG-N.PAG. 1p.

Intelligent evaluation method for identifying favorable shale oil areas based on improved stacked sparse autoencoder.

Authors: Rui Xu Tie Yan Shihui Sun et al.

Source: Oil Shale; 2025, Vol. 42 Issue 1, p79-114, 36p

Subject Terms: SHALE oils, SUPERVISED learning, PETROLEUM prospecting, AUTOENCODERS, MACHINE learning

Wind Speed Prediction of Complex Terrain Based on Multi-Dimensional Time Series Decomposition

Authors: Jingru Sun Yao Zhang Yichuang Sun et al.

Source: IEEE Access, Vol 13, Pp 206475-206489 (2025)

Subject Terms: Wind speed prediction, multivariate time series prediction (MTSP), sparse autoencoder (SAE), Kolmogorov–Arnold network (KAN), time series analysis, BiGRU, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

File Description: electronic resource

Relation: https://ieeexplore.ieee.org/document/11278174/; https://doaj.org/toc/2169-3536

Access URL: https://doaj.org/article/a96978cec89040f48b580902727118fd

Attention-enhanced residual autoencoder for NIR spectral feature extraction and classification of grain varieties.

Authors: Kabiso, Abel Chernet Ko, Cheng-Hao

Source: Scientific Reports; 9/24/2025, Vol. 15 Issue 1, p1-18, 18p

Subject Terms: NEAR infrared spectroscopy, DEEP learning, MACHINE learning, CROP yields, AUTOENCODERS, BIOLOGICAL classification, AGRICULTURE

Prediction of miRNAs and diseases association based on sparse autoencoder and MLP.

Authors: Si-Lin Sun Bing-Wei Zhou Sheng-Zheng Liu et al.

Source: Frontiers in Genetics; 2024, p1-14, 14p

Subject Terms: MULTILAYER perceptrons, MICRORNA, NON-coding RNA, GENE expression, LUPUS erythematosus, MYELOID leukemia

Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders

Authors: Martin Hofmann-Apitius Henri A. Vrooman Reagon Karki et al.

Source: Sci Rep

Subject Terms: 0301 basic medicine, 0303 health sciences, Models, Statistical, Databases, Factual, EMC OR-01, Brain, Bayes Theorem, Parkinson Disease, Polymorphism, Single Nucleotide, EMC NIHES-03-30-02, Article, 3. Good health, Cohort Studies, Translational Research, Biomedical, User-Computer Interface, 03 medical and health sciences, Deep Learning, Alzheimer Disease, Disease Progression, Humans, Computer Simulation, Longitudinal Studies, 14. Life underwater

Access URL: https://www.nature.com/articles/s41598-020-67398-4.pdf
https://pubmed.ncbi.nlm.nih.gov/32620927
https://pure.eur.nl/en/publications/e93c28cb-092b-4e75-b802-ecc2c3bb7aab
https://doi.org/10.1038/s41598-020-67398-4
https://repub.eur.nl/pub/130278
https://repub.eur.nl/pub/130278/Repub_130278_O-A.pdf
https://www.nature.com/articles/s41598-020-67398-4
https://publications.rwth-aachen.de/record/795634
https://ui.adsabs.harvard.edu/abs/2020NatSR..1010971S/abstract
https://www.nature.com/articles/s41598-020-67398-4.pdf

A novel NMF-DiCCA deep learning method and its application in wind turbine blade icing failure identification.

Authors: Chuangyan Yang Peng Li Xun Lang et al.

Source: Maintenance & Reliability / Eksploatacja i Niezawodność; 2024, Vol. 26 Issue 4, p1-14, 14p

Subject Terms: MACHINE learning, SINGULAR value decomposition, LATENT variables, AUTOENCODERS, NONNEGATIVE matrices, WIND turbine blades

3D Keypoint Detection Based on Deep Neural Network with Sparse Autoencoder

Authors: Lin, Xinyu Zhu, Ce Zhang, Qian et al.

Index Terms: Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/1605.00129

Anomaly Detection in Retinal Images using Multi-Scale Deep Feature Sparse Coding

Authors: Das, Sourya Dipta Dutta, Saikat Shah, Nisarg A. et al.

Index Terms: Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/2201.11506

Visual Motion Segmentation in Crowd Videos Based on Spatial-Angular Stacked Sparse Autoencoders.

Authors: Hafeezallah, Adel Al-Dhamari, Ahlam Abu-Bakar, Syed Abd Rahman

Source: Computer Systems Science & Engineering; 2023, Vol. 47 Issue 1, p593-611, 19p

Subject Terms: COLLECTIVE behavior, IMAGE segmentation, DEEP learning, DATA analysis, ACCURACY

An Intelligent Fault Diagnosis Method of Multi-Scale Deep Feature Fusion Based on Information Entropy

Authors: Zhiwu Shang Wanxiang Li Maosheng Gao et al.

Source: Chinese Journal of Mechanical Engineering, Vol 34, Iss 1, Pp 1-16 (2021)

Subject Terms: Fault diagnosis, Feature fusion, Information entropy, Deep autoencoder, Deep belief network, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, TJ1-1570

File Description: electronic resource

Relation: https://doaj.org/toc/1000-9345; https://doaj.org/toc/2192-8258

Access URL: https://doaj.org/article/e73839e8b68543a7937202feee250b34

Multi‐scale feature fusion pyramid attention network for single image dehazing

Authors: Jianlei Liu Peng Liu Yuanke Zhang

Source: IET Image Processing, Vol 17, Iss 9, Pp 2726-2735 (2023)

Subject Terms: attention mechanism, feature fusion, image dehazing, pyramid autoencoder, Photography, TR1-1050, Computer software, QA76.75-76.765

File Description: electronic resource

Relation: https://doaj.org/toc/1751-9659; https://doaj.org/toc/1751-9667

Access URL: https://doaj.org/article/aa36b33883d64a60a8e123c424c054be

Fault Diagnosis for Power Batteries Based on a Stacked Sparse Autoencoder and a Convolutional Block Attention Capsule Network.

Authors: Zhou, Juan Zhang, Shun Wang, Peng

Source: Processes; Apr2024, Vol. 12 Issue 4, p816, 19p

Subject Terms: CAPSULE neural networks, FAULT diagnosis, ELECTRIC vehicle batteries, ELECTRIC vehicles, ELECTRIC power failures, ELECTRIC fault location, FAILURE mode & effects analysis

Deep learning with leagues championship algorithm based intrusion detection on cybersecurity driven industrial IoT systems.

Authors: Alotaibi, Saud S. Alghamdi, Turki Ali

Source: Scientific Reports; 8/19/2025, Vol. 15 Issue 1, p1-17, 17p

Subject Terms: DEEP learning, INTRUSION detection systems (Computer security), AUTOENCODERS, ALGORITHMS, CYBER physical systems, INTERNET security, CYBERTERRORISM, FEATURE selection

Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders.

Authors: Sood, Meemansa Sahay, Akrishta Karki, Reagon et al.

Source: Scientific Reports; 7/3/2020, Vol. 10 Issue 1, p1-14, 14p

Subject Terms: DRUG development, PHARMACEUTICAL research, BAYESIAN analysis, CLINICAL trials, DATA analysis

Mineralized-Anomaly Identification Based on Convolutional Sparse Autoencoder Network and Isolated Forest.

Authors: Yang, Na Zhang, Zhenkai Yang, Jianhua et al.

Source: Natural Resources Research; Feb2023, Vol. 32 Issue 1, p1-18, 18p

Subject Terms: ADDITION (Mathematics), GENERALIZATION, MINERALIZATION, ORE deposits, PRIOR learning

Geographic Terms: SHAANXI Sheng (China), CHINA

Building Recognition Based on Sparse Representation of Spatial Texture and Color Features

Authors: Bin Li Fuqiang Sun Yonghan Zhang

Source: IEEE Access, Vol 7, Pp 37220-37227 (2019)

Subject Terms: Building recognition, texture and color features, extreme learning machine, autoencoder, Sheffield buildings database, sparse representation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

File Description: electronic resource

Relation: https://ieeexplore.ieee.org/document/8667827/; https://doaj.org/toc/2169-3536

Access URL: https://doaj.org/article/4e3177591a6d4871bd4845ebbff2eaca