Search Results - "Sparse stacked autoencoder"

Novel semi-supervised sparse stacked autoencoder integrated with local linear embedding for industrial soft sensing

Authors: Yan-Lin He Yu Jiang Hui-Hui Gao et al.

Source: ISA Transactions.

Cervical cancer classification using sparse stacked autoencoder and fuzzy ARTMAP

Authors: Lawrence Chuin Ming Liaw Shing Chiang Tan Pey Yun Goh et al.

Source: Neural Computing and Applications. 36:13895-13913

Subject Terms: RC71-78.7 Examination. Diagnosis

File Description: text

Hybrid Feature Embedded Sparse Stacked Autoencoder and Manifold Dimensionality Reduction Ensemble for Mental Health Speech Recognition

Authors: Hong Chen Yuan Lin Yongming Li et al.

Source: IEEE Access, Vol 9, Pp 28729-28741 (2021)

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, ensemble learning, feature fusion, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, speech mental health recognition, Embedded hybrid feature sparse stacked autoencoder, L1 regularization, TK1-9971, 3. Good health

Access URL: https://ieeexplore.ieee.org/ielx7/6287639/9312710/09348883.pdf
https://doaj.org/article/4e1029e37cad4c62884db95a4caa020b
https://dblp.uni-trier.de/db/journals/access/access9.html#ChenLLWWL21
https://ieeexplore.ieee.org/document/9348883

Fault classification based on variable‐weighted dynamic sparse stacked autoencoder for industrial processes

Authors: Jie Dong Yanan Tu Kaixiang Peng

Source: The Canadian Journal of Chemical Engineering. 101:420-430

Subject Terms: 02 engineering and technology, 0204 chemical engineering, 0210 nano-technology

Improved Diagnostic Approach for BRB Detection and Classification in Inverter-Driven Induction Motors Employing Sparse Stacked Autoencoder (SSAE) and LightGBM

Authors: Muhammad Amir Khan Bilal Asad Toomas Vaimann et al.

Source: Electronics. 13:1292

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

Fusion of hyperspectral and LiDAR data using sparse stacked autoencoder for land cover classification with 3D-2D convolutional neural network

Authors: Manoj Kumar Singh Shashank Mohan Brajesh Kumar

Source: Journal of Applied Remote Sensing. 16

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

[Psychosis speech recognition algorithm based on deep embedded sparse stacked autoencoder and manifold ensemble]

Authors: Pin Wang Xiaolin Qin Zuwei Zhang et al.

Source: Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi. 38(4)

Subject Terms: Databases, Factual, Psychotic Disorders, 0202 electrical engineering, electronic engineering, information engineering, Speech Perception, Humans, Speech, 02 engineering and technology, Algorithms

Access URL: https://pubmed.ncbi.nlm.nih.gov/34459164
https://www.ncbi.nlm.nih.gov/pubmed/34459164

Sparse stacked autoencoder network for complex system monitoring with industrial applications

Authors: Keke Huang Ziwei Deng Zhaohui Tang et al.

Source: Chaos, Solitons & Fractals. 137:109838

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

Access URL: http://ui.adsabs.harvard.edu/abs/2020CSF...13709838D/abstract
https://ideas.repec.org/a/eee/chsofr/v137y2020ics0960077920302381.html
https://ui.adsabs.harvard.edu/abs/2020CSF...137j9838D/abstract
https://www.sciencedirect.com/science/article/pii/S0960077920302381

Improved Diagnostic Approach for BRB Detection and Classification in Inverter-Driven Induction Motors Employing Sparse Stacked Autoencoder (SSAE) and LightGBM.

Authors: Khan, Muhammad Amir Asad, Bilal Vaimann, Toomas et al.

Source: Electronics (2079-9292); Apr2024, Vol. 13 Issue 7, p1292, 20p

Subject Terms: INDUCTION motors, RECEIVER operating characteristic curves, FAULT diagnosis, FEATURE extraction

Cervical cancer classification using sparse stacked autoencoder and fuzzy ARTMAP.

Authors: Liaw, Lawrence Chuin Ming Tan, Shing Chiang Goh, Pey Yun et al.

Source: Neural Computing & Applications; Aug2024, Vol. 36 Issue 22, p13895-13913, 19p

Subject Terms: TUMOR classification, SUPERVISED learning, CERVICAL cancer, MACHINE learning, EARLY diagnosis, DEEP learning

Decision letter for 'Fault classification based on variable‐weighted dynamic sparse stacked autoencoder for industrial processes'

Review for 'Fault classification based on variable‐weighted dynamic sparse stacked autoencoder for industrial processes'

Review for 'Fault classification based on variable‐weighted dynamic sparse stacked autoencoder for industrial processes'

Author response for 'Fault classification based on variable‐weighted dynamic sparse stacked autoencoder for industrial processes'

Authors: null Jie Dong null Yanan Tu null Kaixiang Peng

Decision letter for 'Fault classification based on variable‐weighted dynamic sparse stacked autoencoder for industrial processes'

Review for 'Fault classification based on variable‐weighted dynamic sparse stacked autoencoder for industrial processes'

Review for 'Fault classification based on variable‐weighted dynamic sparse stacked autoencoder for industrial processes'

Cervical cancer classification using sparse stacked autoencoder and fuzzy ARTMAP

Authors: LCM Liaw SC Tan PY Goh et al.

Subject Terms: Engineering, Information and computing sciences, Artificial intelligence, Computer vision and multimedia computation, Machine learning, Cognitive and computational psychology, Uncategorised value

Relation: http://hdl.handle.net/10779/DRO/DU:28739858.v1; https://figshare.com/articles/journal_contribution/Cervical_cancer_classification_using_sparse_stacked_autoencoder_and_fuzzy_ARTMAP/28739858

Availability: http://hdl.handle.net/10779/DRO/DU:28739858.v1
https://figshare.com/articles/journal_contribution/Cervical_cancer_classification_using_sparse_stacked_autoencoder_and_fuzzy_ARTMAP/28739858

Fault classification based on variable‐weighted dynamic sparse stacked autoencoder for industrial processes.

Authors: Dong, Jie Tu, Yanan Peng, Kaixiang

Source: Canadian Journal of Chemical Engineering; Jan2023, Vol. 101 Issue 1, p420-430, 11p

Subject Terms: MANUFACTURING processes, FISHER discriminant analysis, FAULT diagnosis, INDUSTRY classification, CLASSIFICATION, PRODUCTION increases

Dynamic time warping optimization-based non-intrusive load monitoring for multiple household appliances

Authors: Menghui Li Zhaoyu Tu Jun Wang et al.

Source: International Journal of Electrical Power & Energy Systems, Vol 159, Iss , Pp 110002- (2024)

Subject Terms: Non-intrusive load monitoring, Multi-device tasks, Short time fourier transform, Sparse stacked autoencoder, Dynamic time warping, Production of electric energy or power. Powerplants. Central stations, TK1001-1841

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S0142061524002230; https://doaj.org/toc/0142-0615

Access URL: https://doaj.org/article/b80b4b4ddcdb46de8da566311d63bdd9