Výsledky vyhledávání - Hybrid robust convolutional autoencoder*

Hybrid Attention-Enhanced Regularized Convolutional Autoencoder for Robust EEG Feature Extraction in Seizure Prediction

Autoři: Yu-Hao Chen Hsiang-Yu Chen Yu-Chia Chen a další

Zdroj: IEEE Access, Vol 13, Pp 161053-161072 (2025)

Témata: Seizure prediction, feature extraction, convolutional autoencoder, hybrid attention, regularization, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/11155096/; https://doaj.org/toc/2169-3536

Přístupová URL adresa: https://doaj.org/article/966fe6d7c0a14654a1af2c536e46af53

Hybrid robust convolutional autoencoder for unsupervised anomaly detection of machine tools under noises

Autoři: Yan, Shen Shao, Haidong Xiao, Yiming a další

Zdroj: Robotics and Computer-Integrated Manufacturing. 79

Témata: Machine tools, Deep learning, Unsupervised anomaly detection, Hybrid robust convolutional autoencoder, Noises, Drift och underhållsteknik, Operation and Maintenance

Popis souboru: print

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-92934

Unsupervised Convolutional Transformer Autoencoder for Robust Health Indicator Construction and RUL Prediction in Rotating Machinery

Autoři: Amrit Dahal Hong-Zhong Huang Cheng-Geng Huang a další

Zdroj: Applied Sciences, Vol 15, Iss 20, p 10972 (2025)

Témata: bearings, health indicator, remaining useful life, hybrid convolutional vision transformer, unsupervised learning, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2076-3417/15/20/10972; https://doaj.org/toc/2076-3417

Přístupová URL adresa: https://doaj.org/article/4625722a5f284f1c8741c6b7c1ae9c1b

DHCAE: Deep Hybrid Convolutional Autoencoder Approach for Robust Supervised Hyperspectral Unmixing

Autoři: Fazal Hadi Jingxiang Yang Matee Ullah a další

Zdroj: Remote Sensing, Vol 14, Iss 18, p 4433 (2022)

Témata: hyperspectral unmixing (HSU), hybrid 3D, 2D-convolutional autoencoder (AE) network, supervised, spectral–spatial, remote sensing, Science

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2072-4292/14/18/4433; https://doaj.org/toc/2072-4292

Přístupová URL adresa: https://doaj.org/article/69fbfd032a87448097b06b1e155cb7e2

A hybrid adversarial autoencoder-graph network model with dynamic fusion for robust scRNA-seq clustering

Autoři: Binhua Tang Yingying Feng Xinyu Gao

Zdroj: BMC Genomics, Vol 26, Iss 1, Pp 1-13 (2025)

Témata: ScRNA-seq, Self-supervised clustering, GCN, Adversarial AE, Cross-attention mechanism, Biotechnology, TP248.13-248.65, Genetics, QH426-470

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1471-2164

Přístupová URL adresa: https://doaj.org/article/2a5ea00c188941fbb66094bbf69d63c0

Unsupervised Anomaly Detection in Electric Regulating Valves Using a Hybrid Robust Dual Convolutional Autoencoder with Multi-Channel Vibration Signals

Autoři: Talatibieke Aierken Shuxun Li Mingxing Zheng

Robust Sensor Fault Detection in Wireless Sensor Networks Using a Hybrid Conditional Generative Adversarial Networks and Convolutional Autoencoder

Autoři: Rehan Khan Umer Saeed Insoo Koo

Zdroj: IEEE Sensors Journal. 25:13912-13926

Article Review on: Robust Sensor Fault Detection in Wireless Sensor Networks Using a Hybrid Conditional Generative Adversarial Networks and Convolutional Autoencoder

Autoři: Joshua Martty Delos Santos

Hybrid Graph Convolutional Network With Online Masked Autoencoder for Robust Multimodal Cancer Survival Prediction

Autoři: Wentai Hou Chengxuan Lin Lequan Yu a další

Zdroj: IEEE Transactions on Medical Imaging. 42:2462-2473

Témata: Neoplasms, Humans, Genomics, 3. Good health

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/37028064

Adaptive hybrid convolutional neural network-autoencoder framework for backdoor detection in GenAI-driven semantic communication systems

Autoři: Hassan El Alami Danda B. Rawat

Zdroj: ITU Journal on Future and Evolving Technologies. 6:309-321

Hybrid Deep Convolutional Neural Networks Combined with Autoencoders and Augmented Data to Predict the Look-Up Table 2006

Autoři: Djeddou, Messaoud Hellal, Aouatef Hameed, Ibrahim A. a další

Zdroj: 2024 International Conference on Decision Aid Sciences and Applications (DASA). :1-5

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2408.14626

Revolutionary hybrid ensembled deep learning model for accurate and robust side-channel attack detection in cloud computing

Autoři: C. Lakshminatha Reddy K. Malathi

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-29 (2025)

Témata: Side-channel attacks, Cloud computing, Cryptographic systems, Deep learning, Convolutional neural networks, Long short-term memory, Medicine, Science

Popis souboru: electronic resource

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

Přístupová URL adresa: https://doaj.org/article/4940db52ed7c40a5902a8859818dd136

Disease Classification Using Hybrid Random Forest and Autoencoder on Image-Based Radiology Data

Autoři: Aoudin Daffa Cahya Pratama Manan

Zdroj: Jurnal Indonesia Sosial Sains. 6:2258-2272

A gated temporal attention based intra prediction framework for robust deepfake video detection

Autoři: J. Eric Clapten v. Balaji

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-28 (2025)

Témata: Deepfake detection, Video processing, Deep learning, Intra prediction, Gated temporal attention, Convolutional autoencoder, Medicine, Science

Popis souboru: electronic resource

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

Přístupová URL adresa: https://doaj.org/article/f238bc65ca794bbba11737abe2bb2d6a

Computational prediction of concrete strength via microstructure image analysis: a hybrid machine learning framework

Autoři: Prashant T. Dhorabe Mayuri A. Chandak Boskey V. Bahoria a další

Zdroj: AI in Civil Engineering, Vol 4, Iss 1, Pp 1-16 (2025)

Témata: Attention mechanisms, Convolutional autoencoders, Concrete strength, LSTM networks, Microstructural images, Non-destructive testing, Engineering (General). Civil engineering (General), TA1-2040, Information technology, T58.5-58.64

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2097-0943; https://doaj.org/toc/2730-5392

Přístupová URL adresa: https://doaj.org/article/dc41bfdfbd0e4bd490900eb335704dff

A hybrid 1DCNN-GRU deep learning framework for classifying caprine granulosa cell fertility potential using single-cell transcriptomics.

Autoři: Sananmuang, Thanida Puthier, Denis Chokeshaiusaha, Kaj

Zdroj: Veterinary World. Jul2025, Vol. 18 Issue 7, p1922-1935. 14p.

Témata: Granulosa cells, Fertility, Convolutional neural networks, Transcriptomes, Deep learning, Recurrent neural networks, Goats, Biomarkers

Secure big data sharing with hybrid encryption and deep learning

Autoři: Reshma Siyal Jun Long Sajid Ullah Khan a další

Zdroj: Journal of King Saud University: Computer and Information Sciences, Vol 37, Iss 8, Pp 1-29 (2025)

Témata: Siamese convolutional neural network, Deep stacked autoencoder, Relief method, Attack detection, Multiple data security, Blockchain security, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1319-1578; https://doaj.org/toc/2213-1248

Přístupová URL adresa: https://doaj.org/article/a12b36e47bb7495da7b7b6a7d822b2a8

HYBRID HAAR CASCADE AND CNN+EDL FRAMEWORK FOR ROBUST FACIAL EXPRESSION RECOGNITION IN HUMAN–COMPUTER INTERACTION

Autoři: Shanthakumari R Babu M Sharavanan S a další

Zdroj: ICTACT Journal on Communication Technology. 16:3652-3663

Wind Power Turbine Fault Detection using Hybridized Convolutional Neural Network and Autoencoder

Autoři: T. Ahilan Saurabh Sinha Serhii Nekrasov a další

Zdroj: Journal of Circuits, Systems and Computers.

A Hybrid Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM)–Attention Model Architecture for Precise Medical Image Analysis and Disease Diagnosis.

Autoři: Hayat, Md. Tanvir Allawi, Yazan M. Alamro, Wasan a další

Zdroj: Diagnostics (2075-4418); Nov2025, Vol. 17 Issue 21, p2673, 32p

Témata: CONVOLUTIONAL neural networks, LONG short-term memory, DIAGNOSIS, COMPUTER-assisted image analysis (Medicine), FEATURE selection, DEEP learning, CLASSIFICATION