Search Results - class-specific deep autoencoder~

Sample reconstruction with deep autoencoder for one sample per person face recognition

Authors: Yan Zhang Hua Peng

Source: IET Computer Vision, Vol 11, Iss 6, Pp 471-478 (2017)

Subject Terms: 4. Education, Computer applications to medicine. Medical informatics, R858-859.7, 0211 other engineering and technologies, OSPP face recognition, 02 engineering and technology, class-specific deep autoencoder, QA76.75-76.765, multisample subject to single-sample subject intraclass variations, CDA, one sample per person face recognition, 0202 electrical engineering, electronic engineering, information engineering, Computer software, sample reconstruction, 10. No inequality

Access URL: https://doaj.org/article/760c7173812b459682d146d586f85181
https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-cvi.2016.0322
https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2016.0322
https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-cvi.2016.0322
https://dblp.uni-trier.de/db/journals/iet-cvi/iet-cvi11.html#ZhangP17
https://doi.org/10.1049/iet-cvi.2016.0322

Two-Phase Multitask Autoencoder-Based Deep Learning Framework for Subject-Independent EEG Motor Imagery Classification

Authors: Changgyun Jin Andrew H. Song Seong-Eun Kim

Source: IEEE Access, Vol 12, Pp 77356-77367 (2024)

Subject Terms: Classification, deep learning, EEG, motor imagery, multitask autoencoder, subject-independent, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

File Description: electronic resource

Relation: https://ieeexplore.ieee.org/document/10540565/; https://doaj.org/toc/2169-3536

Access URL: https://doaj.org/article/e224854d86d643978058e2430c63f522

Data-driven deep learning approach for suggesting process parameters for the milling operations.

Authors: Asghar, Eram Ratti, Andrea Tolio, Tullio

Source: Procedia CIRP. 2024, Vol. 130, p307-312. 6p.

FAIR-Net: A Fuzzy Autoencoder and Interpretable Rule-Based Network for Ancient Chinese Character Recognition.

Authors: Ge, Yanling Zhang, Yunmeng Roh, Seok-Beom

Source: Sensors (14248220); Sep2025, Vol. 25 Issue 18, p5928, 18p

Subject Terms: OPTICAL character recognition, FUZZY neural networks, PATTERN recognition systems, DEEP learning, CULTURAL maintenance, FEATURE extraction

Enhanced prediction of recombination hotspots using input features extracted by class specific autoencoders.

Authors: Nath, Abhigyan Karthikeyan, S.

Source: Journal of Theoretical Biology. May2018, Vol. 444, p73-82. 10p.

Subject Terms: *GEOLOGIC hot spots, *MAMMALS, *MACHINE learning, *RANDOM forest algorithms, *YEAST

Video classification using deep autoencoder network

Authors: Hajati, F. (Farshid) Tavakolian, M. (Mohammad)

Index Terms: info:eu-repo/semantics/article, info:eu-repo/semantics/acceptedVersion

URL: http://urn.fi/urn:nbn:fi-fe202102266056

A novel motor bearing fault diagnosis method based on a deep sparse binary autoencoder and principal component analysis.

Authors: Yunzhong Xia Wanxiang Li Yangyang Gao

Source: Insight: Non-Destructive Testing & Condition Monitoring; Apr2023, Vol. 65 Issue 4, p217-225, 9p

Subject Terms: FAULT diagnosis, PRINCIPAL components analysis, DIAGNOSIS, ROLLER bearings, COMPLEX variables

Are you eligible? Predicting adulthood from face images via Class Specific Mean Autoencoder.

Authors: Singh, Maneet Nagpal, Shruti Vatsa, Mayank et al.

Source: Pattern Recognition Letters. Mar2019, Vol. 119, p121-130. 10p.

Subject Terms: *LOGICAL prediction, *MACHINE learning, *FEATURE extraction, *BIOMETRIC identification, *PROBLEM solving

Online Bengali handwritten numerals recognition using Deep Autoencoders

Authors: Balasubramanian, Vineeth N

Source: 2016 22nd National Conference on Communication, NCC 2016

Index Terms: Conference paper

URL: https://raiith.krc.iith.ac.in/handle/123456789/60472

BSCGAN: structured minority class image generation under class-balanced pretraining.

Authors: Wan, Qian Zhou, Bin Wang, Yanjiang

Source: Visual Computer. Apr2025, Vol. 41 Issue 6, p3853-3865. 13p.

Subject Terms: *GENERATIVE adversarial networks, *DATA structures, *DATA distribution, *AUTOENCODERS, *DEEP learning

Online Bengali Handwritten Numerals Recognition Using Deep Autoencoders

Authors: Pal, A Khonglah, B K Mandal, S et al.

Index Terms: Engineering technology, Telecommunication, Conference or Workshop Item, PeerReviewed

URL: http://raiith.iith.ac.in/2965/
http://raiith.iith.ac.in/2965

Are you eligible? Predicting adulthood from face images via class specific mean autoencoder

Authors: Singh, Maneet Nagpal, Shruti Vatsa, Mayank et al.

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

URL: http://arxiv.org/abs/1803.07385

Online Bengali handwritten numerals recognition using Deep Autoencoders

Authors: H. L. Rufiner Arghya Pal Himakshi Choudhury et al.

Source: 2016 Twenty Second National Conference on Communication (NCC). :1-6

Subject Terms: 0301 basic medicine, 03 medical and health sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/7561181/
https://raiith.iith.ac.in/2965/

Video Classification Using Deep Autoencoder Network

Authors: Farshid Hajati Mohammad Tavakolian

Source: Advances in Intelligent Systems and Computing ISBN: 9783030223533

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, 4. Education, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

File Description: application/pdf

Access URL: http://jultika.oulu.fi/files/nbnfi-fe202102266056.pdf
https://link.springer.com/chapter/10.1007%2F978-3-030-22354-0_45
https://doi.org/10.1007/978-3-030-22354-0_45
https://rd.springer.com/chapter/10.1007/978-3-030-22354-0_45
https://research-repository.griffith.edu.au/handle/10072/403005
https://link.springer.com/10.1007/978-3-030-22354-0_45
https://dblp.uni-trier.de/db/conf/cisis/cisis2019.html#HajatiT19
http://urn.fi/urn:nbn:fi-fe202102266056

A Combination of Deep Autoencoder and Multi-Scale Residual Network for Landslide Susceptibility Evaluation.

Authors: Wang, Zhuolu Xu, Shenghua Liu, Jiping et al.

Source: Remote Sensing; Feb2023, Vol. 15 Issue 3, p653, 22p

Subject Terms: LANDSLIDES, LANDSLIDE hazard analysis, CONVOLUTIONAL neural networks, EMERGENCY management, LANDSLIDE prediction, DEEP learning

Geographic Terms: SHAANXI Sheng (China)

D³FC: deep feature-extractor discriminative dictionary-learning fuzzy classifier for medical imaging.

Authors: Ghasemi, Majid Kelarestaghi, Manoochehr Eshghi, Farshad et al.

Source: Applied Intelligence; May2022, Vol. 52 Issue 7, p7201-7217, 17p

Subject Terms: DIAGNOSTIC imaging, IMAGE analysis, DEEP learning, SURVIVAL rate

FARMSAR: Fixing AgRicultural Mislabels Using Sentinel-1 Time Series and AutoencodeRs

Authors: Thomas Di Martino Régis Guinvarc’h Laetitia Thirion-Lefevre et al.

Source: Remote Sensing, Vol 15, Iss 1, p 35 (2022)

Subject Terms: autoencoder, deep learning, SAR, time-series, agriculture, label noise, Science

File Description: electronic resource

Relation: https://www.mdpi.com/2072-4292/15/1/35; https://doaj.org/toc/2072-4292

Access URL: https://doaj.org/article/518992fad66549009a101180edda2ec1

Two-Stream Deep Architecture for Hyperspectral Image Classification.

Authors: Hao, Siyuan Wang, Wei Ye, Yuanxin et al.

Source: IEEE Transactions on Geoscience & Remote Sensing. Apr2018, Vol. 56 Issue 4, p2349-2361. 13p.

Subject Terms: *HYPERSPECTRAL imaging systems, *CLASSIFICATION, *ARTIFICIAL neural networks, *DEEP learning, *REMOTE sensing, *PIXELS

Elevator Fault Detection Using Profile Extraction and Deep Autoencoder Feature Extraction for Acceleration and Magnetic Signals.

Authors: Mishra, Krishna Mohan Huhtala, Kalevi

Source: Applied Sciences (2076-3417); 8/1/2019, Vol. 9 Issue 15, p2990, 15p

Subject Terms: FEATURE extraction, ELEVATORS

Memory Defense: More Robust Classification via a Memory-Masking Autoencoder

Authors: Adhikarla, Eashan Luo, Dan Davison, Brian D.

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

URL: http://arxiv.org/abs/2202.02595