Výsledky vyhledávání - sparse convolutional autoencoder (cae)

Convolutional autoencoder-augmented sparse identification of noisy nonlinear fluid dynamics from unlabelled data.

Autoři: Zhang, Meng Zeng, Fanfan Yousif, Mustafa Z. a další

Zdroj: Physics of Fluids; Sep2025, Vol. 37 Issue 9, p1-15, 15p

Témata: FLUID dynamics, AUTOENCODERS, NONLINEAR mechanics, FLOW simulations, TURBULENT flow, METADATA, SPARSE approximations, NOISE control

Leveraging variant of CAE with sparse convolutional embedding and two-stage application-driven data augmentation for image clustering.

Autoři: Liu, Yanming Liu, Jinglei

Zdroj: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Feb2025, Vol. 29 Issue 3, p1419-1435, 17p

Témata: DATA augmentation, AUTOENCODERS

Sparse deep encoded features with enhanced sinogramic red deer optimization for fault inspection in wafer maps.

Autoři: Altantawy, Doaa A. Yakout, Mohamed A.

Zdroj: Journal of Intelligent Manufacturing. Jun2025, Vol. 36 Issue 5, p3359-3397. 39p.

Témata: *MANUFACTURING processes, *INFORMATION processing, CONVOLUTIONAL neural networks, OPTIMIZATION algorithms, AUTOENCODERS

Estimation of Damaged Surface Images in Drilled Unidirectional Carbon Fiber Reinforced Polymer Sheets Using Convolutional Autoencoder and Multi-Layer Perceptron Decoder.

Autoři: Kurniawan, Eddy Hur, Yong Chan Kim, Ji Hoon

Zdroj: Fibers & Polymers; Dec2025, Vol. 26 Issue 12, p5647-5660, 14p

Multi-resolution reconstruction of longitudinal streambed footprints using embedded sparse convolutional autoencoders

Autoři: Yang, Yifan Tang, Zihao 邵东 a další

Přispěvatelé: Yang, Yifan Tang, Zihao 邵东 a další

Témata: Machine learning, Streambed footprint, Convolutional autoencoder, Multi-resolution reconstruction, RIVER, PROBABILITY, MODEL, Engineering, Geology, Water Resources, Civil, Geosciences, Multidisciplinary, 一类

Relation: JOURNAL OF HYDROLOGY; http://dspace.imech.ac.cn/handle/311007/100158; http://dspace.imech.ac.cn/handle/311007/100159

Dostupnost: http://dspace.imech.ac.cn/handle/311007/100158
http://dspace.imech.ac.cn/handle/311007/100159
https://doi.org/10.1016/j.jhydrol.2025.132852

Sensor-Driven Surrogate Modeling and Control of Nonlinear Dynamical Systems Using FAE-CAE-LSTM and Deep Reinforcement Learning

Autoři: Kherad, M. Moayyedi, M. K. Fotouhi-Ghazvini, F. a další

Zdroj: Sensors. 25(16)

Témata: Autoencoders, Control Of Dynamical Systems, Cyber-physical Systems, Deep Reinforcement Learning, Long Short-term Memory, Sensor-driven Modeling, Circular Cylinders, Computer Control Systems, Convolution, Dynamical Systems, Dynamics, Embedded Systems, Flow Control, Fuel Additives, Nonlinear Dynamical Systems, Real Time Control, Robust Control, Auto Encoders, Control Of Dynamical System, Cybe-physical Systems, High-dimensional, Higher-dimensional, Reinforcement Learning Agent, Reinforcement Learnings, Short Term Memory

Popis souboru: print

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-73172
https://doi.org/10.3390/s25165149

Domain-Adaptive Direction of Arrival (DOA) Estimation in Complex Indoor Environments Based on Convolutional Autoencoder and Transfer Learning.

Autoři: Shen, Lingyu Li, Jianfeng Pan, Jingjing a další

Zdroj: Sensors (14248220); May2025, Vol. 25 Issue 10, p2959, 24p

Témata: AUTOENCODERS, DEEP learning, FEATURE extraction, SMART homes, WIRELESS communications

Unsupervised sparse convolutional autoencoder for multi-class change detection in hyperspectral images

Autoři: Bergamasco, Luca Bovolo, Francesca Bruzzone, Lorenzo

Přispěvatelé: Bergamasco, Luca Bovolo, Francesca Bruzzone, Lorenzo

Témata: Convolutional Autoencoder, Hyperspectral image, Multi-class Change Detection, Spectral Unmixing, Unsupervised Change Detection

Popis souboru: ELETTRONICO

Relation: ispartofbook:Proceedings of SPIE - The International Society for Optical Engineering; Artificial Intelligence and Image and Signal Processing for Remote Sensing XXX 2024; volume:13196; serie:PROCEEDINGS OF SPIE; alleditors:Bruzzone, Lorenzo; https://hdl.handle.net/11572/444099

Dostupnost: https://hdl.handle.net/11572/444099
https://doi.org/10.1117/12.3030005

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

Autoři: Nageswara Rao, B. Acharya, U. Rajendra Tan, Ru-San a další

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

Out-of-Roundness Wheel Damage Identification in Railway Vehicles Using AutoEncoder Models

Autoři: Renato Melo Rafaelle Finotti António Guedes a další

Zdroj: Applied Sciences ; Volume 15 ; Issue 5 ; Pages: 2662

Témata: structural health monitoring, railways, damage detection, out of roundness, sparse autoencoder, convolutional autoencoder, variational autoencoder

Geografické téma: agris

Popis souboru: application/pdf

Relation: Civil Engineering; https://dx.doi.org/10.3390/app15052662

Dostupnost: https://doi.org/10.3390/app15052662

Temperature scaling unmixing framework based on convolutional autoencoder

Autoři: Jin Xu Mingming Xu Shanwei Liu a další

Zdroj: International Journal of Applied Earth Observations and Geoinformation, Vol 129, Iss , Pp 103864- (2024)

Témata: Hyperspectral unmixing, Convolutional autoencoder, Sparsity constraint, Temperature scaling, Equal-frequency binning, Physical geography, GB3-5030, Environmental sciences, GE1-350

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1569843224002188; https://doaj.org/toc/1569-8432

Přístupová URL adresa: https://doaj.org/article/aa7533b7fbf447e1a8b51942e4c8c5f4

Motor Fault Diagnosis and Detection with Convolutional Autoencoder (CAE) Based on Analysis of Electrical Energy Data.

Autoři: Choi, YuRim Joe, Inwhee

Zdroj: Electronics (2079-9292); Oct2024, Vol. 13 Issue 19, p3946, 29p

Témata: ARTIFICIAL neural networks, REAL-time computing, ELECTRIC faults, FAULT diagnosis, SYSTEM analysis, ELECTRIC motors

Surrogate Modeling of Hydrogen-Enriched Combustion Using Autoencoder-Based Dimensionality Reduction.

Autoři: Zhang, Lanfei Chu, Xu Ding, Siyu a další

Zdroj: Processes; Apr2025, Vol. 13 Issue 4, p1093, 21p

Témata: AUTOENCODERS, JET nozzles, ENGINEERING design, FLUID flow, SPATIAL resolution, DEEP learning

Deep Learning Augmented Data Assimilation: Reconstructing Missing Information with Convolutional Autoencoders.

Autoři: Wang, Yueya Shi, Xiaoming Lei, Lili a další

Zdroj: Monthly Weather Review; Aug2022, Vol. 150 Issue 8, p1977-1991, 15p, 3 Diagrams, 2 Charts, 5 Graphs

Témata: DEEP learning, NUMERICAL weather forecasting, BAROTROPIC equation, REMOTE sensing, SQUARE root

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

Out-of-Roundness Wheel Damage Identification in Railway Vehicles Using AutoEncoder Models.

Autoři: Melo, Renato Finotti, Rafaelle Guedes, António a další

Zdroj: Applied Sciences (2076-3417); Mar2025, Vol. 15 Issue 5, p2662, 25p

Témata: STRUCTURAL health monitoring, AUTOENCODERS, RAILROAD safety measures, RAILROAD trains, COMPARATIVE studies

Out-of-roundness damage wheel idenficaon in railway vehicles using autoencoder models

Autoři: Melo, Renato da Silva Cury, Alexandre Abrahão http://lattes.cnpq.br/1092810690505352 a další

Přispěvatelé: Melo, Renato da Silva Cury, Alexandre Abrahão http://lattes.cnpq.br/1092810690505352 a další

Témata: Monitoramento de integridade estrutural, Ferrovias, Detecção de danos, Ovalização, Autocodificador esparso, Autocodificador convolucional, Autocodificador variacional, Structural health monitoring, Railways, Damage detection, Out-of-roundness, Sparse autoencoder, Convolutional autoencoder, Variational autoencoder, CNPQ::ENGENHARIAS

Popis souboru: application/pdf

Relation: https://repositorio.ufjf.br/jspui/handle/ufjf/18552

Dostupnost: https://repositorio.ufjf.br/jspui/handle/ufjf/18552

An efficient model for diabetic detection using heuristic approach based serial cascaded convolutional ensemble network.

Autoři: Bejugam, Santosh Kumar Vankara, Jyothi

Zdroj: Artificial Intelligence Review; Oct2025, Vol. 58 Issue 10, p1-43, 43p

TriMap thermography with convolutional autoencoder for enhanced defect detection of polymer composites.

Autoři: Liu, Yi Zheng, Mingkai Liu, Kaixin a další

Zdroj: Journal of Applied Physics; 4/14/2022, Vol. 131 Issue 14, p1-9, 9p

Témata: THERMOGRAPHY, CARBON fiber-reinforced plastics, IMAGE analysis, FEATURE extraction, POLYMERS

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

Autoři: Ogundokun, Roseline Oluwaseun Owolawi, Pius Adewale Tu, Chunling a další

Zdroj: Tomography: A Journal for Imaging Research; Aug2025, Vol. 11 Issue 8, p91, 22p

Témata: AUTOENCODERS, ENSEMBLE learning, DEEP learning, FEATURE extraction, CANCER diagnosis, HISTOPATHOLOGY, MACHINE learning