Výsledky vyhledávání - Sparse autoencoder~

Channel Estimation and Pilot Design for Uplink Sparse Code Multiple Access System Based on Complex-Valued Sparse Autoencoder

Autoři: Quan Yuan Dezhi Li Zhenyong Wang a další

Zdroj: IEEE Access, Vol 13, Pp 123559-123569 (2025)

Témata: Sparse code multiple access, Internet of Things, channel estimation, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, massive connection, sparse pilot structure, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, complex-valued sparse autoencoder, TK1-9971

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/6514899/08667100.pdf
https://doaj.org/article/fbe5140ccf6b4575b898c315f16c8e7b
https://ieeexplore.ieee.org/document/8667100/

Non-Line-of-Sight Multipath Classification Method for BDS Using Convolutional Sparse Autoencoder with LSTM

Autoři: Qin, Yahang Li, Zhenni Xie, Shengli a další

Zdroj: Tsinghua Science and Technology. 30:68-86

Témata: Satellites, Multipath classification, BeiDou Navigation Satellite System (BDS), Solid modeling, Three-dimensional displays, Long short-term memory (LSTM), Convolutional sparse autoencoder, Interference, Urban areas, Convolution, Long short term memory

An Enhanced Intrusion Detection System Using Attention-Based Stacked Sparse Autoencoder Feature Extraction

Autoři: Venkata Ramani Varanasi Razia Shaik

Zdroj: Engineering, Technology & Applied Science Research. 15:24436-24441

ESAE-SDA: ensemble sparse autoencoder framework for epigenomics-informed snoRNA-disease associations prediction

Autoři: Xinqing Jiang Xiaojun Chen Lifeng Xu a další

Zdroj: BMC Bioinformatics, Vol 26, Iss 1, Pp 1-18 (2025)

Témata: Epigenomics, snoRNA-disease associations (SDAs), Ensemble learning framework, Sparse autoencoder, Dynamically sampling, Artificial intelligence (AI), Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1471-2105

Přístupová URL adresa: https://doaj.org/article/4a1813752009454491f25e2b31390236

Self-Regularization with Sparse Autoencoders for Controllable LLM-based Classification

Autoři: Xuansheng Wu Wenhao Yu Xiaoming Zhai a další

Zdroj: Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2. :3250-3260

Témata: FOS: Computer and information sciences, Computation and Language, Computation and Language (cs.CL)

Přístupová URL adresa: http://arxiv.org/abs/2502.14133

A deep learning framework with hybrid stacked sparse autoencoder for type 2 diabetes prediction

Autoři: Abdussamad Hanita Daud Rajalingam Sokkalingam a další

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

Témata: Autoencoder, Deep learning, Diabetes prediction, Feature selection, Machine learning, Sparse data, Medicine, Science

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2045-2322

Přístupová URL adresa: https://doaj.org/article/2fea4da469ce4f14bd82089d355a10f4

Intelligent guidance system for the visually impaired person using a lightweight YOLOv4-based object detection and sparse autoencoder framework

Autoři: Alaa O. Khadidos Ayman Yafoz

Zdroj: Journal of the Chinese Institute of Engineers. :1-21

SAGEA: Sparse Autoencoder-based Group Embeddings Aggregation for Fairness-Preserving Group Recommendations

Autoři: Vít Koštejn Ladislav Peška Martin Spišák

Zdroj: Proceedings of the Nineteenth ACM Conference on Recommender Systems. :1290-1295

Drive-by damage detection and localization exploiting continuous wavelet transform and multiple sparse autoencoders

Autoři: Lorenzo Bernardini Francesco Morgan Bono Andrea Collina

Zdroj: Railway Engineering Science, Vol 33, Iss 4, Pp 721-745 (2025)

Témata: Drive-by, Sparse autoencoder, Steel truss railway bridge, Continuous wavelet transform, Damage detection, Damage localization, Railroad engineering and operation, TF1-1620

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2662-4745; https://doaj.org/toc/2662-4753

Přístupová URL adresa: https://doaj.org/article/36553b70af354470bfab169610f35260

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

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

Real-Time Cloud Intrusion Detection with SpinalSAENet: A Sparse Autoencoder Approach with Focal Loss Optimization

Autoři: null N. Savitha

Zdroj: Journal of Information Systems Engineering and Management. 10:54-69

Research on a face data processing method based on sparse autoencoder neural networks

Autoři: Zhipeng Chen Shenda Yu

Zdroj: IET Conference Proceedings. 2024:325-330

A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders

Autoři: Jorge Magalhães Tomás Jorge Rúben Silva a další

Přispěvatelé: Jorge Magalhães Tomás Jorge Rúben Silva a další

Zdroj: Railway Engineering Science, Vol 32, Iss 4, Pp 421-443 (2024)

Témata: Railroad engineering and operation, Wayside condition monitoring, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, TF1-1620, Damage identification, Passenger trains, OOR wheel damage, Sparse autoencoder, 0201 civil engineering

Popis souboru: application/pdf

Přístupová URL adresa: https://doaj.org/article/3756a7b582fe4bbca9b9a96603091c57
https://hdl.handle.net/10216/166705

GRU‐based stacked sparse autoencoder with attention mechanism for process monitoring

Autoři: Zengdi Miao Ping Wu Zhenquan Wu a další

Zdroj: The Canadian Journal of Chemical Engineering. 103:3767-3785

Sparse Autoencoder Insights on Voice Embeddings

Autoři: Pluth, Daniel Zhou, Yu Gurbani, Vijay K.

Zdroj: 2025 Conference on Artificial Intelligence x Multimedia (AIxMM). :1-6

Témata: FOS: Computer and information sciences, Computer Science - Computation and Language, Computation and Language (cs.CL)

Přístupová URL adresa: http://arxiv.org/abs/2502.00127

XAI-DSCSA: explainable-AI-based deep semi-supervised convolutional sparse autoencoder for facial expression recognition

Autoři: M. Mohana P. Subashini George Ghinea

Zdroj: Signal, Image and Video Processing. 19

Témata: autoencoder, semi-supervised learning, convolutional sparse autoencoder, facial expression recognition, feature representation, unsupervised learning

Přístupová URL adresa: https://bura.brunel.ac.uk/handle/2438/31141

Mammo-SAE : Interpreting Breast Cancer Concept Learning with Sparse Autoencoders

Autoři: Nakka, Krishna Kanth

Zdroj: Lecture Notes in Computer Science ISBN: 9783032055583

Témata: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Vision and Pattern Recognition

Přístupová URL adresa: http://arxiv.org/abs/2507.15227

Time-Inferred Sparse Autoencoder for Improved Full-Field Reconstruction from Sparse Measurements

Autoři: Nitin Nagesh Kulkarni Alessandro Sabato

Zdroj: Computer Vision & Laser Vibrometry, Vol. 6 ISBN: 9788743804277

Latent Feature‐Based Type 2 Diabetes Prediction Using a Hybrid Stacked Sparse Autoencoder and Machine Learning Models

Autoři: Abdussamad Hanita Daud Rajalingam Sokkalingam a další

Zdroj: Engineering Reports, Vol 7, Iss 9, Pp n/a-n/a (2025)

Témata: autoencoder, hybrid model, machine learning models, sparse data, Type 2 diabetes prediction, Engineering (General). Civil engineering (General), TA1-2040, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2577-8196

Přístupová URL adresa: https://doaj.org/article/ce842a66c11744049ad6331118fec323

Local Entropy Based Remora Optimization and Sparse Autoencoders for Cancer Diagnosis Through Microarray Gene Expression Analysis

Autoři: N. Bharanidharan S. R. Sannasi Chakravarthy Vinoth Kumar Venkatesan a další

Zdroj: IEEE Access, Vol 12, Pp 39285-39299 (2024)

Témata: 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, sparse autoencoder, remora optimization, deep learning, Electrical engineering. Electronics. Nuclear engineering, entropy, Cancer, dimensionality reduction, TK1-9971, 3. Good health

Přístupová URL adresa: https://doaj.org/article/7ab98ced2df543f4a7786cd88221ce0e