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

Single sample face recognition using deep learning: a survey.

Authors: Tomar, Vivek Kumar, Nitin Srivastava, Ayush Raj

Source: Artificial Intelligence Review; Oct2023 Suppl 1, Vol. 56, p1063-1111, 49p

Subject Terms: FACE perception, DEEP learning, RESEARCH personnel

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

Deep Convolutional Neural Network Used in Single Sample per Person Face Recognition.

Authors: Zeng, Junying Zhao, Xiaoxiao Gan, Junying et al.

Source: Computational Intelligence & Neuroscience; 8/23/2018, p1-11, 11p

Subject Terms: FACE perception, HUMAN facial recognition software, COMPUTER vision, NEURAL circuitry, DEEP learning

Complex, Intelligent, and Software Intensive Systems

Authors: Leonard Barolli Farookh Khadeer Hussain Makoto Ikeda

Resource Type: eBook.

Subjects: Soft computing--Congresses, Artificial intelligence--Congresses

Categories: COMPUTERS / Artificial Intelligence / General, TECHNOLOGY & ENGINEERING / Engineering (General)