Výsledky vyhledávání - Layered sparse autoencoder*

Hybrid Greylag Goose deep learning with layered sparse network for women nutrition recommendation during menstrual cycle

Autoři: E. Logapriya Surendran Rajendran Mohammad Zakariah

Zdroj: Sci Rep
Scientific Reports, Vol 15, Iss 1, Pp 1-22 (2025)

Témata: Greylag Goose optimization, Science, Deep learning, Bidirectional gated recurrent unit, Pre-processing, Article, Layered sparse autoencoder, Deep Learning, Geese, Medicine, Humans, Female, Neural Networks, Computer, Menstrual cycle, Menstrual Cycle, Algorithms

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/39966547
https://doaj.org/article/1fdc03bab0db474c8ebe8a2b866bf2e9

Hybrid Greylag Goose deep learning with layered sparse network for women nutrition recommendation during menstrual cycle.

Autoři: Logapriya, E. Rajendran, Surendran Zakariah, Mohammad

Zdroj: Scientific Reports; 2/18/2025, Vol. 15 Issue 1, p1-22, 22p

Témata: OPTIMIZATION algorithms, DEEP learning, AUTOENCODERS, NUTRITIONAL requirements, FEATURE extraction, MENSTRUATION, MENSTRUAL cycle

Comparing Functional and Effective Connectivity Features in Diagnosis of Autism Spectrum Disorder Using Stacked Autoencoder by Resting-State fMRI Data.

Autoři: Navaei, Pegah Khadem, Ali Zaferani, Effat Jalaeian

Zdroj: Frontiers in Biomedical Technologies; Autumn2025, Vol. 12 Issue 4, p830-843, 14p

Témata: AUTISM spectrum disorders, FUNCTIONAL connectivity, AUTOENCODER, ARTIFICIAL neural networks, FUNCTIONAL magnetic resonance imaging, GRANGER causality test

Supervised Learning via Unsupervised Sparse Autoencoder

Autoři: Jianran Liu Chan Li Wenyuan Yang

Zdroj: IEEE Access, Vol 6, Pp 73802-73814 (2018)

Témata: sparse autoencoder, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, feature representation, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, supervised learning, dimensionality reduction, TK1-9971

Přístupová URL adresa: https://doaj.org/article/b3d938628d9041e997fd31b0edceac81
http://ieeexplore.ieee.org/document/8558569
https://ieeexplore.ieee.org/document/8558569
https://dblp.uni-trier.de/db/journals/access/access6.html#LiuLY18a

Three layered sparse dictionary learning algorithm for enhancing the subject wise segregation of brain networks.

Autoři: Khalid MU Nauman MM Akram S a další

Zdroj: Scientific reports [Sci Rep] 2024 Aug 17; Vol. 14 (1), pp. 19070. Date of Electronic Publication: 2024 Aug 17.

Způsob vydávání: Journal Article

Informace o časopise: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

Výrazy ze slovníku MeSH: Magnetic Resonance Imaging*/methods , Algorithms* , Brain*/diagnostic imaging , Brain*/physiology, Humans ; Image Processing, Computer-Assisted/methods ; Brain Mapping/methods ; Nerve Net/physiology ; Nerve Net/diagnostic imaging ; Machine Learning

Anomaly detection for blueberry data using sparse autoencoder-support vector machine

Autoři: Dianwen Wei Jian Zheng Hongchun Qu

Zdroj: PeerJ Computer Science, Vol 9, p e1214 (2023)

Témata: Anomaly detection, Auto encoder, High dimensionality, Support vector machine, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://peerj.com/articles/cs-1214.pdf; https://peerj.com/articles/cs-1214/; https://doaj.org/toc/2376-5992

Přístupová URL adresa: https://doaj.org/article/02e7be96dcec425998535c74971bc4c9

Attention-based convolutional dual sparse autoencoder for analyzing air, water and heat stress in poultry farms for egg production.

Autoři: Deepika Nagarathna Channegowda

Zdroj: Multimedia Tools & Applications; Apr2025, Vol. 84 Issue 14, p14105-14137, 33p

Témata: FISHER discriminant analysis, POULTRY farms, LINEAR programming, POULTRY farming, AUTOENCODERS, EGG quality, FOOD quality

Sparse semi-autoencoders to solve the vanishing information problem in multi-layered neural networks.

Autoři: Kamimura, Ryotaro Takeuchi, Haruhiko

Zdroj: Applied Intelligence; Jul2019, Vol. 49 Issue 7, p2522-2545, 24p

Témata: ARTIFICIAL neural networks, DECISION theory, EYE tracking, INFORMATION networks, PRUNING

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

Autoři: Rui Xu Tie Yan Shihui Sun a další

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

Témata: SHALE oils, SUPERVISED learning, PETROLEUM prospecting, AUTOENCODERS, MACHINE learning

CoCoChain: A Concept-Aware Consensus Protocol for Secure Sensor Data Exchange in Vehicular Ad Hoc Networks.

Autoři: Juárez, Rubén Nicolas-Sans, Ruben Tamames, José Fernández

Zdroj: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p6226, 51p

Témata: VEHICULAR ad hoc networks, BLOCKCHAINS, MOBILE communication systems, DATA transmission systems, DATA integrity, AUTOENCODERS

IoT and cloud computing-based automated epileptic seizure detection using optimized Siamese convolutional sparse autoencoder network.

Autoři: Ramkumar, M. Jamaesha, S. Syed Gowtham, M. S. a další

Zdroj: Signal, Image & Video Processing; Jun2024, Vol. 18 Issue 4, p3509-3525, 17p

An Adaptive Regressor with Layered Featuring Based on Federated Learning.

Autoři: Zhao, Chuan'gang Li, Yang Sun, Bin a další

Zdroj: Electronics (2079-9292); Jul2025, Vol. 14 Issue 13, p2573, 25p

Témata: FEDERATED learning, ARTIFICIAL intelligence, DATA privacy, DEEP learning, ENVIRONMENTAL monitoring, AGRICULTURAL forecasts

Detection of human movement by combining supervised machine learning and an embroidered textile capacitance sensor.

Autoři: Kim, Ji-seon Kim, Jooyong

Zdroj: Textile Research Journal; Feb2025, Vol. 95 Issue 3/4, p305-322, 18p

Témata: SUPERVISED learning, MACHINE learning, STANDARD deviations, AUTOENCODERS, ARTIFICIAL intelligence

Renovated Random Attribute-Based Fennec Fox Optimized Deep Learning Framework in Low-Rate DoS Attack Detection in IoT.

Autoři: Balaji, Prasanalakshmi Babu, Sangita Ma, Maode a další

Zdroj: Computers, Materials & Continua; 2025, Vol. 84 Issue 3, p5831-5858, 28p

Témata: DENIAL of service attacks, DEEP learning, INTERNET of things, AUTOENCODERS, OPTIMIZATION algorithms, FEATURE extraction

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

Autoři: Alotaibi, Saud S. Alghamdi, Turki Ali

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

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

An Effective Heart Disease Prediction Model Using Deep Learningbased Dimensionality Reduction on Imbalanced Data.

Autoři: Kabirirad, S. Afshin, V. Zahiri, S. H.

Zdroj: Journal of Electrical & Computer Engineering Innovations (JECEI); Jul2025, Vol. 13 Issue 2, p317-329, 13p

Témata: DIMENSIONAL reduction algorithms, AUTOENCODERS, PRINCIPAL components analysis, FEATURE extraction, HEART diseases

CResDAE: A Deep Autoencoder with Attention Mechanism for Hyperspectral Unmixing.

Autoři: Zhao, Chong Wang, Jinlin Qiao, Qingqing a další

Zdroj: Remote Sensing; Nov2025, Vol. 17 Issue 21, p3622, 28p

Témata: AUTOENCODERS, GEOLOGICAL surveys, HYPERSPECTRAL imaging systems, SURFACE properties, REMOTE-sensing images, PROSPECTING

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

Autoři: Jagat, Rikhi Ram Sisodia, Dilip Singh Singh, Pradeep

Zdroj: Neural Computing & Applications; Aug2023, Vol. 35 Issue 24, p17883-17898, 16p

Témata: BLOGS, ROBOTS, DEEP learning, COMPUTER software, RANDOM forest algorithms, DECISION trees, SUPERVISED learning

A Hybrid Deep Learning Model for E‐Commerce Recommendations: Sentiment Analysis With Autoencoders and Generative Adversarial Networks.

Autoři: Yarjanli, Mohammad Mahdinasab, Neda Murray, Richard

Zdroj: International Journal of Intelligent Systems; 10/2/2025, Vol. 2025, p1-36, 36p

Témata: SENTIMENT analysis, DEEP learning, GENERATIVE adversarial networks, FEATURE extraction, ELECTRONIC commerce, AUTOENCODERS

Nonredundant sparse feature extraction using autoencoders with receptive fields clustering.

Autoři: Ayinde, Babajide O. Zurada, Jacek M.

Zdroj: Neural Networks. Sep2017, Vol. 93, p99-109. 11p.

Témata: *FEATURE extraction, *DEEP learning, *CLUSTER analysis (Statistics), *PATTERN recognition systems, *ARTIFICIAL neural networks