Search Results - Stacked semi-supervised autoencoder

Stacked semi-supervised autoencoder-regularized RVFLNs for reliable prediction of molten iron quality in blast furnace

Authors: Ping Zhou Peng Zhao Zihui Ou et al.

Source: Neural Computing and Applications. 37:10425-10438

Entropy Stacked Autoencoder based Diffusion Model (ESADM) and Fuzzy Clustering with Semi Supervised Fuzzy Graph Convolutional Network (FC-SSFGCN) for Rail Surface Defect Detection

Authors: Samyuktha Sasi Sekaran Dr.M. Subaji

Source: Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications. 15:17-35

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.

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, Vol 42, Iss 1, Pp 79-114 (2025)

Subject Terms: autoencoder, semi-supervised learning, Technology, Q1-390, Science (General), batch normalization, shale oil, favorable area

Stacked Dual-Guided Autoencoder: A Scalable Deep Latent Variable Model for Semi-Supervised Industrial Soft Sensing

Authors: Zeyu Yang Tingting Hu Le Yao et al.

Source: IEEE Transactions on Instrumentation and Measurement. 73:1-14

Web-S4AE: a semi-supervised stacked sparse autoencoder model for web robot detection

Authors: Rikhi Ram Jagat Dilip Singh Sisodia Pradeep Singh

Source: Neural Computing and Applications. 35:17883-17898

A fault diagnosis framework for rotating machinery of marine equipment: A semi-supervised learning framework based on contractive stacked autoencoder

Authors: Penghao Pan Dong Zhao Yueyang Li

Source: Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment. 237:625-636

Subject Terms: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Ground Target Recognition Using Carrier-Free UWB Radar Sensor With a Semi-Supervised Stacked Convolutional Denoising Autoencoder

Authors: Yuying Zhu Shuning Zhang Xiaoxiong Li et al.

Source: IEEE Sensors Journal. 21:20685-20693

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

Access URL: https://ieeexplore.ieee.org/document/9495777/
http://ui.adsabs.harvard.edu/abs/2021ISenJ..2120685Z/abstract

A Semi-Supervised Stacked Autoencoder Using the Pseudo Label for Classification Tasks

Authors: Jie Lai Xiaodan Wang Qian Xiang et al.

Source: Entropy, Vol 25, Iss 9, p 1274 (2023)

Subject Terms: deep learning, semi-supervised learning, stacked autoencoder, pseudo label, regularization, Science, Astrophysics, QB460-466, Physics, QC1-999

File Description: electronic resource

Relation: https://www.mdpi.com/1099-4300/25/9/1274; https://doaj.org/toc/1099-4300

Access URL: https://doaj.org/article/c1e42ee082384e7aa1c3595b558191f6

Representation learning via a semi-supervised stacked distance autoencoder for image classification

Authors: Liang Hou Xiao-yi Luo Zi-yang Wang et al.

Source: Frontiers of Information Technology & Electronic Engineering. 21:1005-1018

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

Access URL: https://journal.hep.com.cn/ckcest/fitee/CN/10.1631/FITEE.1900116
https://link.springer.com/article/10.1631/FITEE.1900116
https://dblp.uni-trier.de/db/journals/jzusc/jzusc21.html#HouLWL20

A Semi-supervised Stacked Autoencoder Approach for Network Traffic Classification

Authors: Kandaraj Piamrat Dhruvjyoti Bagadthey Ons Aouedi

Source: 2020 IEEE 28th International Conference on Network Protocols (ICNP). :1-6

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

Access URL: https://hal.archives-ouvertes.fr/hal-02933689v2/file/CR2_SAE.pdf
https://hal.archives-ouvertes.fr/hal-02933689/document
https://hal.archives-ouvertes.fr/hal-03049711
https://dblp.uni-trier.de/db/conf/icnp/icnp2020.html#AouediPB20
https://www.computer.org/csdl/proceedings-article/icnp/2020/09259390/1oUCKPqfr9u

Semi-supervised stacked autoencoder-based deep hierarchical semantic feature for real-time fingerprint liveness detection

Authors: Peipeng Yu Xingming Sun Chen Xianyi et al.

Source: Journal of Real-Time Image Processing. 17:55-71

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

Access URL: https://link.springer.com/article/10.1007/s11554-019-00928-0
https://doi.org/10.1007/s11554-019-00928-0
https://link.springer.com/10.1007/s11554-019-00928-0
https://dblp.uni-trier.de/db/journals/jrtip/jrtip17.html#YuanCYMCWS20

Handling partially labeled network data: A semi-supervised approach using stacked sparse autoencoder

Authors: Ons Aouedi Kandaraj Piamrat Dhruvjyoti Bagadthey et al.

Contributors: Ons Aouedi Kandaraj Piamrat Dhruvjyoti Bagadthey et al.

Source: Computer Networks. 207:108742

Subject Terms: semi-supervised learning, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], feature extraction, deep learning, 02 engineering and technology, [INFO] Computer Science [cs], partial information, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Machine learning, stacked sparse autoencoder, 0202 electrical engineering, electronic engineering, information engineering, [INFO]Computer Science [cs], traffic classification

File Description: application/pdf

Access URL: https://hal.archives-ouvertes.fr/hal-03524935/file/Comnet%20%282%29.pdf
https://hal.science/hal-03524935v1
https://doi.org/10.1016/j.comnet.2021.108742
https://hal.science/hal-03524935v1/document

A soft sensor model based on an improved semi-supervised stacked autoencoder for just-in-time updating of cement clinker production process data f-CaO

Authors: Wei Zheng Hui Liu XiaoYu Zhou et al.

Source: Measurement Science and Technology. 35:056203

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0204 chemical engineering

Missing Structural and Clinical Features Imputation for Semi-supervised Alzheimer's Disease Classification using Stacked Sparse Autoencoder

Authors: M. Omair Ahmad Mallappa Kumara Swamy Emimal Jabason

Source: 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS). :1-4

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Access URL: https://dblp.uni-trier.de/db/conf/biocas/biocas2018.html#JabasonAS18

Semi-Supervised Cross-Subject Emotion Recognition Based on Stacked Denoising Autoencoder Architecture Using a Fusion of Multi-Modal Physiological Signals

Authors: Junhai Luo Yuxin Tian Hang Yu et al.

Source: Entropy, Vol 24, Iss 5, p 577 (2022)

Subject Terms: DEAP dataset, electroencephalogram (EEG), emotion recognition, multi-source fusion, stacked denoising autoencoder, unsupervised representation learning, Science, Astrophysics, QB460-466, Physics, QC1-999

File Description: electronic resource

Relation: https://www.mdpi.com/1099-4300/24/5/577; https://doaj.org/toc/1099-4300

Access URL: https://doaj.org/article/24e9ac76404c4c4fb90c2425f36fcfdd

Stacked Autoencoders Driven by Semi-Supervised Learning for Building Extraction from near Infrared Remote Sensing Imagery

Authors: Eftychios Protopapadakis Anastasios Doulamis Nikolaos Doulamis et al.

Source: Remote Sensing, Vol 13, Iss 3, p 371 (2021)

Subject Terms: semi-supervised learning, deep learning, stack autoencoders, building detection, remote sensing, semantic segmentation, Science

File Description: electronic resource

Relation: https://www.mdpi.com/2072-4292/13/3/371; https://doaj.org/toc/2072-4292

Access URL: https://doaj.org/article/cd15bfe4145a455bbb00617947fb93f9

Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals

Authors: Anupriya Gogna Angshul Majumdar Rabab K. Ward

Source: IEEE Transactions on Biomedical Engineering. 64:2196-2205

Subject Terms: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, Information Storage and Retrieval, Signal Processing, Computer-Assisted, 02 engineering and technology, Pattern Recognition, Automated, Machine Learning (cs.LG), Electrocardiography, 03 medical and health sciences, 0302 clinical medicine, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Supervised Machine Learning, Electrical Engineering and Systems Science - Signal Processing, Algorithms

Access URL: http://arxiv.org/pdf/1912.12127
https://pubmed.ncbi.nlm.nih.gov/27893378
http://arxiv.org/abs/1912.12127
https://dblp.uni-trier.de/db/journals/corr/corr1912.html#abs-1912-12127
https://doi.org/10.1109/TBME.2016.2631620
https://europepmc.org/abstract/MED/27893378
http://dblp.uni-trier.de/db/journals/tbe/tbe64.html#GognaMW17
http://arxiv.org/pdf/1912.12127.pdf
https://arxiv.org/abs/1912.12127

Semi-supervised classification with stacked autoencoder

Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals

Authors: Gogna, Anupriya Majumdar, Angshul Ward, Rabab

Index Terms: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/1912.12127