Výsledky vyhledávání - deep adversarial convolution autoencoder network

Enhanced Prediction of the Remaining Useful Life of Rolling Bearings Under Cross-Working Conditions via an Initial Degradation Detection-Enabled Joint Transfer Metric Network

Autoři: Lingfeng Qi Jiafang Pan Tianping Huang a další

Zdroj: Applied Sciences, Vol 15, Iss 12, p 6401 (2025)

Témata: remaining useful life prediction, reconstruction along projection pathway, deep adversarial convolution autoencoder network, joint domain adaptation loss, 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/2076-3417/15/12/6401; https://doaj.org/toc/2076-3417

Přístupová URL adresa: https://doaj.org/article/e5b80ed94f004b17a3ca4adee50fd0fc

A Visual Computing Unified Application Using Deep Learning and Computer Vision Techniques.

Autoři: B. J., Sowmya Meeradevi Seema, S. a další

Zdroj: International Journal of Interactive Mobile Technologies. 2024, Vol. 18 Issue 1, p59-74. 16p.

Témata: Deep learning, Computer vision, Machine learning, Generative adversarial networks, Artificial intelligence, Convolutional neural networks

On the use of Denoising Autoencoders and Deep Convolutional Adversarial Networks for Automated Removal of Date Stamps

Autoři: Anderson, Nicolas Paavola, Mikael Sognnes, Johnny

Dostupnost: http://hdl.handle.net/11250/2618711

Enhanced Prediction of the Remaining Useful Life of Rolling Bearings Under Cross-Working Conditions via an Initial Degradation Detection-Enabled Joint Transfer Metric Network.

Autoři: Qi, Lingfeng Pan, Jiafang Huang, Tianping a další

Zdroj: Applied Sciences (2076-3417); Jun2025, Vol. 15 Issue 12, p6401, 26p

Témata: REMAINING useful life, ROLLER bearings, AUTOENCODERS, ROTATING machinery, DATA distribution

DRAN: Deep recurrent adversarial network for automated pancreassegmentation.

Autoři: Ning, Yang Han, Zhongyi Zhong, Li a další

Zdroj: IET Image Processing (Wiley-Blackwell); May2020, Vol. 14, p1091-1100, 10p

Research on Digital Camouflage Pattern Generation Algorithm Based on Adversarial Autoencoder Network.

Autoři: Yang, Xin Xu, Wei-Dong Jia, Qi a další

Zdroj: International Journal of Pattern Recognition & Artificial Intelligence. Jun2020, Vol. 34 Issue 6, pN.PAG-N.PAG. 15p.

Témata: *EUCLIDEAN distance, *ALGORITHMS, *LATENT variables, *COLOR vision, *COLORS

Fortifying vision models: A comprehensive survey of defences against adversarial examples.

Autoři: Kumar, Siddheshwar Srivastava, Shashank Banerjea, Shashwati

Zdroj: Applied Soft Computing. Dec2025:Part A, Vol. 185, pN.PAG-N.PAG. 1p.

Témata: Machine learning, Generative adversarial networks, Computer vision, Statistical reliability, Artificial neural networks, University research

GEnDDn: An lncRNA-Disease Association Identification Framework Based on Dual-Net Neural Architecture and Deep Neural Network.

Autoři: Peng L Ren M Huang L a další

Zdroj: Interdisciplinary sciences, computational life sciences [Interdiscip Sci] 2024 Jun; Vol. 16 (2), pp. 418-438. Date of Electronic Publication: 2024 May 11.

Způsob vydávání: Journal Article

Informace o časopise: Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 101515919 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1867-1462 (Electronic) Linking ISSN: 18671462 NLM ISO Abbreviation: Interdiscip Sci Subsets: MEDLINE

Výrazy ze slovníku MeSH: RNA, Long Noncoding*/genetics , Neural Networks, Computer*, Humans ; Deep Learning ; Computational Biology/methods ; Algorithms ; Neoplasms/genetics

AACNet: attention aided CNN-autoencoder network for precise categorization of respiratory conditions from HRCT scans.

Autoři: Kakati, Anchita Bhattacharjya, Upasana Medhi, Jyoti Prakash a další

Zdroj: Network Modeling & Analysis in Health Informatics & Bioinformatics; 8/20/2025, Vol. 14 Issue 1, p1-29, 29p

Knowledge-driven deep learning for fast MR imaging: Undersampled MR image reconstruction from supervised to un-supervised learning.

Autoři: Wang S Wu R Jia S a další

Zdroj: Magnetic resonance in medicine [Magn Reson Med] 2024 Aug; Vol. 92 (2), pp. 496-518. Date of Electronic Publication: 2024 Apr 16.

Způsob vydávání: Journal Article; Review

Informace o časopise: Publisher: Wiley Country of Publication: United States NLM ID: 8505245 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1522-2594 (Electronic) Linking ISSN: 07403194 NLM ISO Abbreviation: Magn Reson Med Subsets: MEDLINE

Výrazy ze slovníku MeSH: Deep Learning* , Magnetic Resonance Imaging*/methods , Image Processing, Computer-Assisted*/methods , Neural Networks, Computer* , Algorithms*, Humans ; Supervised Machine Learning ; Brain/diagnostic imaging

Dual-Pyramidal Image Inpainting With Dynamic Normalization.

Autoři: Wang, Chao Shao, Mingwen Meng, Deyu a další

Zdroj: IEEE Transactions on Circuits & Systems for Video Technology. Sep2022, Vol. 32 Issue 9, p5975-5988. 14p.

Témata: INPAINTING, FEATURE extraction, GENERATIVE adversarial networks

LN-MRSCAE: A novel deep learning based denoising method for mechanical vibration signals.

Autoři: Du, Wenliao Yang, Lingkai Wang, Hongchao a další

Zdroj: Journal of Vibration & Control; Feb2024, Vol. 30 Issue 3/4, p459-471, 13p

Témata: DEEP learning, VIBRATION (Mechanics), LEARNING modules, SIGNAL denoising

SKFont: skeleton-driven Korean font generator with conditional deep adversarial networks.

Autoři: Ko, Debbie Honghee Hassan, Ammar Ul Suk, Jungjae a další

Zdroj: International Journal on Document Analysis & Recognition; Dec2021, Vol. 24 Issue 4, p325-337, 13p

Témata: DEEP learning, GENERATIVE adversarial networks

Robust steganographic approach using generative adversarial network and compressive autoencoder.

Autoři: Qasaimeh, Malik Qtaish, Alaa Abu Aljawarneh, Shadi

Zdroj: Multimedia Tools & Applications; Aug2025, Vol. 84 Issue 26, p31479-31516, 38p

Témata: GENERATIVE adversarial networks, DEEP learning, DATA security, CRYPTOGRAPHY, IMAGE processing, AUTOENCODERS

A novel intelligent multicross domain fault diagnosis of servo motor-bearing system based on Domain Generalized Graph Convolution Autoencoder.

Autoři: Zhao, Xiaoli Hu, Yuanhao Liu, Jiahui a další

Zdroj: Structural Health Monitoring; May2025, Vol. 24 Issue 3, p1485-1499, 15p

Témata: AUTOENCODERS, FAULT diagnosis, DEEP learning, REPRESENTATIONS of graphs, ROLLER bearings

A Deep Learning-Based Method for Mechanical Equipment Unknown Fault Detection in the Industrial Internet of Things.

Autoři: Liu, Xiaokai Meng, Xiangheng Ning, Lina a další

Zdroj: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p5984, 26p

Témata: DEEP learning, FAULT diagnosis, INDUSTRY 4.0, CONVOLUTIONAL neural networks, AUTOENCODERS, LONG short-term memory, OUTLIER detection, MACHINE learning

Multi-Head Graph Attention Adversarial Autoencoder Network for Unsupervised Change Detection Using Heterogeneous Remote Sensing Images.

Autoři: Jia, Meng Lou, Xiangyu Zhao, Zhiqiang a další

Zdroj: Remote Sensing; Aug2025, Vol. 7 Issue 15, p2581, 29p

Témata: REMOTE sensing, AUTOENCODERS, CHANGE-point problems, IMAGE reconstruction, IMAGE processing, GRAPH neural networks

A QUANTUM CONVOLUTION AUTOENCODER FOR HANDWRITTEN LETTERS AND DIGITS: A CASE STUDY.

Autoři: SAWERWAIN, MAREK KOWAL, MAREK KORBICZ, JÓZEF

Zdroj: International Journal of Applied Mathematics & Computer Science; 2025, Vol. 35 Issue 4, p651-666, 16p

Innovative Noise Extraction and Denoising in Low-Dose CT Using a Supervised Deep Learning Framework.

Autoři: Zhang, Wei Salmi, Abderrahmane Yang, Chifu a další

Zdroj: Electronics (2079-9292); Aug2024, Vol. 13 Issue 16, p3184, 22p

Témata: CONVOLUTIONAL neural networks, GENERATIVE adversarial networks, NOISE control, SUPERVISED learning, SIGNAL-to-noise ratio, DEEP learning

Cascaded hybrid convolutional autoencoder network for spectral-spatial nonlinear hyperspectral unmixing.

Autoři: Wu, Jinbin Zhao, Jiankang Long, Haihui

Zdroj: International Journal of Remote Sensing; Dec2024, Vol. 45 Issue 24, p9267-9286, 20p

Témata: AUTOENCODERS, DEEP learning, IMAGE reconstruction, SELF-perception, PHOTONS