Výsledky vyhľadávania - Hybrid robust convolutional autoencoder~

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

Autori: Yu-Hao Chen Hsiang-Yu Chen Yu-Chia Chen a ďalší

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

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

Popis súboru: electronic resource

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

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

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

Autori: Yan, Shen Shao, Haidong Xiao, Yiming a ďalší

Zdroj: Robotics and Computer-Integrated Manufacturing. 79

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

Popis súboru: print

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

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

Autori: Fazal Hadi Jingxiang Yang Matee Ullah a ďalší

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

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

Popis súboru: electronic resource

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

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

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

Autori: Talatibieke Aierken Shuxun Li Mingxing Zheng

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

Autori: 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

Autori: Joshua Martty Delos Santos

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

Autori: J. Eric Clapten v. Balaji

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

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

Popis súboru: electronic resource

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

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

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

Autori: Sananmuang, Thanida Puthier, Denis Chokeshaiusaha, Kaj

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

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

Weighted salp swarm algorithm with deep learning-powered cyber-threat detection for robust network security

Autori: Maha M. Althobaiti José Escorcia‐Gutierrez

Zdroj: AIMS Mathematics, Vol 9, Iss 7, Pp 17676-17695 (2024)

Predmety: Artificial intelligence, Computer Networks and Communications, 02 engineering and technology, Pattern recognition (psychology), 7. Clean energy, Swarm behaviour, Anomaly Detection in High-Dimensional Data, 03 medical and health sciences, Characterization and Detection of Android Malware, Deep Learning, 0302 clinical medicine, Artificial Intelligence, Computer security, Machine learning, network security, QA1-939, 0202 electrical engineering, electronic engineering, information engineering, salp swarm algorithm, cyber threat, Deep learning, Network security, Computer science, convolutional autoencoder, Intrusion Detection, Network Security, Algorithm, intrusion detection systems, Computer Science, Physical Sciences, Signal Processing, Network Intrusion Detection and Defense Mechanisms, Security Analysis, Botnet Detection, Mathematics

Prístupová URL adresa: https://doaj.org/article/70ff11a1d438471ba0570f1e62c30cef

Studies from National Taiwan Normal University Add New Findings in the Area of Engineering (Hybrid Attention-Enhanced Regularized Convolutional Autoencoder for Robust EEG Feature Extraction in Seizure Prediction).

Zdroj: Pain & Central Nervous System Week. 10/6/2025, p2557-2557. 1p.

Lightweight Real-Time Anomaly Detection and Prediction for Surveillance Videos Using a Self-Supervised Hybrid Autoencoder and Dynamic Graph CNN-LSTM Framework

Autori: Abdulla S. AlShamsi Najah AbuAli

Zdroj: IEEE Access, Vol 13, Pp 195423-195435 (2025)

Predmety: Anomaly detection, autoencoder, graph neural networks, real-time surveillance, self-supervised learning, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis súboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/11241206/; https://doaj.org/toc/2169-3536

Prístupová URL adresa: https://doaj.org/article/4adf79e3ac9f4aa0990e9b995cec99f6

Convolutional autoencoder-based deep learning for intracerebral hemorrhage classification using brain CT images.

Autori: Nageswara Rao, B. Acharya, U. Rajendra Tan, Ru-San a ďalší

Zdroj: Cognitive Neurodynamics; 5/19/2025, Vol. 19 Issue 1, p1-13, 13p

TriDeepRec: a hybrid deep learning approach to content- and behavior-based recommendation systems.

Autori: Ghadami, Amirhossein Tran, Thomas

Zdroj: User Modeling & User-Adapted Interaction. Nov2024, Vol. 34 Issue 5, p2085-2114. 30p.

Predmety: *STANDARD deviations, *CUSTOMER relations, *RECOMMENDER systems, DEEP learning, BLENDED learning

Autoencoder-Assisted Stacked Ensemble Learning for Lymphoma Subtype Classification: A Hybrid Deep Learning and Machine Learning Approach

Autori: Roseline Oluwaseun Ogundokun Pius Adewale Owolawi Chunling Tu a ďalší

Zdroj: Tomography, Vol 11, Iss 8, p 91 (2025)

Predmety: lymphoma classification, autoencoder, stacked ensemble learning, deep feature extraction, digital pathology, machine learning, Computer applications to medicine. Medical informatics, R858-859.7

Popis súboru: electronic resource

Relation: https://www.mdpi.com/2379-139X/11/8/91; https://doaj.org/toc/2379-1381; https://doaj.org/toc/2379-139X

Prístupová URL adresa: https://doaj.org/article/c77263e08b7a4d529c5606976485af2c

Bridging Content and Behavior: A Deep Dive into Hybrid Recommendation Systems for Enhancing Personalized User Experiences

Autori: Ghadami, Amirhossein

Predmety: Deep Learning, Recommendation System, Hybrid Recommendation System, Convolutional Autoencoder, Cold Start

Deep Convolutional Autoencoder for Assessment of Drive-Cycle Anomalies in Connected Vehicle Sensor Data

Autori: Geglio, Anthony Hedayati, Eisa Tascillo, Mark a ďalší

Témy: Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, C.3, I.2.1, I.2.6, I.5.1, text

URL: http://arxiv.org/abs/2202.07592

Optimizing dotted Arabic expiration date recognition with ARABEX: a convolutional autoencoder with bidirectional LSTM and CRNN approach.

Autori: Zaki, Hozaifa Soliman, Ghada

Zdroj: International Journal on Document Analysis & Recognition; Dec2025, Vol. 28 Issue 4, p555-572, 18p

An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets.

Autori: Salehiyan, Ahmad Moghaddam, Pardis Sadatian Kaveh, Masoud

Zdroj: Future Internet. Jul2025, Vol. 17 Issue 7, p279. 34p.

Predmety: Intrusion detection systems (Computer security), Edge computing, Autoencoder, Internet security, Cyber physical systems, Deep learning, Generative adversarial networks

A Hybrid Framework for Red Blood Cell Labeling Using Elliptical Fitting, Autoencoding, and Data Augmentation

Autori: Bundasak Angmanee Surasak Wanram Amorn Thedsakhulwong

Zdroj: Journal of Imaging, Vol 11, Iss 9, p 309 (2025)

Predmety: red blood cell morphology, autoencoder, ellipse fitting, unsupervised clustering, data augmentation, anemia, Photography, TR1-1050, Computer applications to medicine. Medical informatics, R858-859.7, Electronic computers. Computer science, QA75.5-76.95

Popis súboru: electronic resource

Relation: https://www.mdpi.com/2313-433X/11/9/309; https://doaj.org/toc/2313-433X

Prístupová URL adresa: https://doaj.org/article/e14191f4309d4b179bcb80753f2fb5a7

Dose Reduction in Scintigraphic Imaging Through Enhanced Convolutional Autoencoder-Based Denoising.

Autori: Bouzianis, Nikolaos Stathopoulos, Ioannis Valsamaki, Pipitsa a ďalší

Zdroj: Journal of Imaging; Jun2025, Vol. 11 Issue 6, p197, 28p