Výsledky vyhledávání - sparse deep convolutional autoencoder

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

SPAER: Sparse Deep Convolutional Autoencoder Model to Extract Low Dimensional Imaging Biomarkers for Early Detection of Breast Cancer Using Dynamic Thermography

Autoři: Bardia Yousefi Hamed Akbari Michelle Hershman a další

Zdroj: Applied Sciences, Vol 11, Iss 7, p 3248 (2021)

Témata: breast cancer, thermography, sparse deep convolutional autoencoder, matrix factorization, dimensionality reduction, thermomics, 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/2076-3417/11/7/3248; https://doaj.org/toc/2076-3417

Přístupová URL adresa: https://doaj.org/article/3c70757effa743f3b9bef5e4d264eb2f

A novel multichannel sparse convolutional autoencoder for electrocardiogram signal compression.

Autoři: Bekiryazıcı, Tahir Damkacı, Mehmet Aydemir, Gürkan a další

Zdroj: Journal of Electrocardiology. Nov2025, Vol. 93, pN.PAG-N.PAG. 1p.

DOA estimation method for sparse arrays based on deep convolutional autoencoder and deep convolutional neural network.

Autoři: Guo, Shuhan Zhang, Qin Fu, Xiaolong a další

Zdroj: Digital Signal Processing. Jan2026:Part D, Vol. 168, pN.PAG-N.PAG. 1p.

SPAER: Sparse Deep Convolutional Autoencoder Model to Extract Low Dimensional Imaging Biomarkers for Early Detection of Breast Cancer Using Dynamic Thermography.

Autoři: Yousefi, Bardia Akbari, Hamed Hershman, Michelle a další

Zdroj: Applied Sciences (2076-3417); Apr2021, Vol. 11 Issue 7, p3248, 15p

Témata: EARLY detection of cancer, THERMOGRAPHY, MATRIX decomposition, DEEP learning, INFRARED imaging, NONNEGATIVE matrices

Automatic Baseline Correction of 1D Signals Using a Parameter-Free Deep Convolutional Autoencoder Algorithm.

Autoři: Górski, Łukasz Jakubowska, Małgorzata

Zdroj: Applied Sciences (2076-3417); Nov2025, Vol. 15 Issue 22, p12069, 18p

Témata: AUTOENCODERS, ANALYTICAL chemistry, DEEP learning, ALGORITHMS, SIGNAL processing

Integrating multi-source monitoring data and deep convolutional autoencoder technology for slope failure pattern recognition.

Autoři: Han, Nana Miao, Wending Li, Mingzhi a další

Zdroj: Frontiers in Earth Science; 2025, p1-11, 11p

Témata: PATTERN recognition systems, SLOPES (Soil mechanics), AUTOENCODERS, INDUSTRIAL safety, FAILURE mode & effects analysis, LANDSLIDES

A Deep Convolutional Autoencoder–Enabled Channel Estimation Method in Intelligent Wireless Communication Systems.

Autoři: Tian, Xinyu Jiang, Weiwei

Zdroj: International Journal of Intelligent Systems; 10/30/2024, Vol. 2024, p1-12, 12p

Témata: WIRELESS communications, CHANNEL estimation, SIGNAL detection, DEEP learning, DEMODULATION, WIRELESS channels, TRANSMITTERS (Communication)

Unsupervised Learning for Machinery Adaptive Fault Detection Using Wide-Deep Convolutional Autoencoder with Kernelized Attention Mechanism.

Autoři: Yan, Hao Si, Xiangfeng Liang, Jianqiang a další

Zdroj: Sensors (14248220); Dec2024, Vol. 24 Issue 24, p8053, 19p

Témata: FAULT diagnosis, AUTOENCODERS, INDUSTRIAL applications, SCREWS, MACHINERY, DEEP learning

Fast Dual Deep Convolutional Autoencoder Network for Denoising Monte Carlo Rendering.

Autoři: Alzbier, Ahmed Mustafa Taha Chunyi Chen Zhongye Shen a další

Zdroj: Journal of Imaging Science & Technology; May/Jun2023, Vol. 67 Issue 3, p1-12, 12p

Témata: DEEP learning, CONVOLUTIONAL neural networks, PIXELS, IMAGE reconstruction, SIGNAL-to-noise ratio

Modeling Task fMRI Data via Deep Convolutional Autoencoder

Autoři: Heng Huang Xintao Hu Yu Zhao a další

Zdroj: Lecture Notes in Computer Science ISBN: 9783319590493

Témata: 2. Zero hunger, 03 medical and health sciences, Deep Learning, 0302 clinical medicine, Connectome, Brain, Humans, Magnetic Resonance Imaging, Unsupervised Machine Learning

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/28641247
https://link.springer.com/chapter/10.1007%2F978-3-319-59050-9_33
https://pubmed.ncbi.nlm.nih.gov/28641247/
http://ieeexplore.ieee.org/document/7949140/
https://xplqa30.ieee.org/document/7949140/
https://www.ncbi.nlm.nih.gov/pubmed/28641247
https://ieeexplore.ieee.org/document/7949140
https://dblp.uni-trier.de/db/conf/ipmi/ipmi2017.html#HuangHMDZH0L17
https://link.springer.com/10.1007/978-3-319-59050-9_33
https://doi.org/10.1007/978-3-319-59050-9_33
http://doi.org/10.1007/978-3-319-59050-9_33

Fast and scalable distributed deep convolutional autoencoder for fMRI big data analytics

Autoři: Milad Makkie Heng Huang Yu Zhao a další

Zdroj: Neurocomputing. 325:20-30

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, Machine Learning (stat.ML), Machine Learning (cs.LG), 03 medical and health sciences, 0302 clinical medicine, Computer Science - Distributed, Parallel, and Cluster Computing, Statistics - Machine Learning, Quantitative Biology - Neurons and Cognition, FOS: Biological sciences, Neurons and Cognition (q-bio.NC), Distributed, Parallel, and Cluster Computing (cs.DC), Neural and Evolutionary Computing (cs.NE)

Přístupová URL adresa: https://europepmc.org/articles/pmc6660166?pdf=render
https://pubmed.ncbi.nlm.nih.gov/31354187
http://arxiv.org/abs/1710.08961
http://arxiv.org/pdf/1710.08961.pdf
https://dblp.uni-trier.de/db/journals/corr/corr1710.html#abs-1710-08961
https://arxiv.org/abs/1710.08961
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6660166
https://pubmed.ncbi.nlm.nih.gov/31354187/
http://www.diva-portal.org/smash/record.jsf?pid=diva2:1255524

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

Fast and scalable distributed deep convolutional autoencoder for fMRI big data analytics

Autoři: Makkie, M Huang, H Zhao, Y a další

Témata: Journal Article

URL: http://hdl.handle.net/10453/139547
Neurocomputing
10.1016/j.neucom.2018.09.066

High-Resolution SAR Image Classification via Deep Convolutional Autoencoders

Autoři: Jianchao Fan Baoming Li Fuliang Chen a další

Zdroj: IEEE Geoscience and Remote Sensing Letters. 12:2351-2355

Témata: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 10. No inequality, 16. Peace & justice

TumorEncode - Deep Convolutional Autoencoder for Computed Tomography Tumor Treatment Assessment

Autoři: Dominik Nörenberg Michael Sühling and Horst-Michael Gros a další

Zdroj: 2018 International Joint Conference on Neural Networks (IJCNN). :1-8

Témata: 03 medical and health sciences, 0302 clinical medicine, 3. Good health

Sparse Representations for Object- and Ego-Motion Estimations in Dynamic Scenes

Autoři: Kashyap, Hirak J Fowlkes, Charless C Krichmar, Jeffrey L

Zdroj: IEEE Transactions on Neural Networks and Learning Systems. 32(6)

Témata: Information and Computing Sciences, Computer Vision and Multimedia Computation, Estimation, Dynamics, Optical imaging, Cameras, Training, Adaptive optics, Motion segmentation, Convolutional autoencoder, ego motion, object motion, overcomplete basis, sparse representation, cs.CV, cs.LG, Artificial Intelligence & Image Processing, Artificial intelligence

Popis souboru: application/pdf

Přístupová URL adresa: https://escholarship.org/uc/item/7p53p8zv
https://escholarship.org/content/qt7p53p8zv/qt7p53p8zv.pdf

Mine Microseismic Signal Denoising Based on a Deep Convolutional Autoencoder.

Autoři: Hu, Ting Xu, Bin Wang, Yongfa a další

Zdroj: Shock & Vibration; 8/30/2023, p1-15, 15p

Témata: DEEP learning, SIGNAL denoising, HILBERT-Huang transform, SIGNAL-to-noise ratio, FOURIER transforms, AUDITORY masking, MINE safety

DLSIA: Deep Learning for Scientific Image Analysis

Autoři: Roberts, Eric J Chavez, Tanny Hexemer, Alexander a další

Zdroj: Journal of Applied Crystallography. 57(2)

Témata: 3402 Inorganic Chemistry (for-2020), 34 Chemical Sciences (for-2020), 3406 Physical Chemistry (for-2020), 51 Physical Sciences (for-2020), 5104 Condensed Matter Physics (for-2020), Bioengineering (rcdc), Biomedical Imaging (rcdc), Machine Learning and Artificial Intelligence (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), deep learning, convolutional neural networks, X-ray scattering, tomography, data compression, X-ray scattering, convolutional neural networks, data compression, deep learning, tomography, 01 Mathematical Sciences (for), 02 Physical Sciences (for), 09 Engineering (for), Inorganic & Nuclear Chemistry (science-metrix), 3402 Inorganic chemistry (for-2020), 3406 Physical chemistry (for-2020), 5104 Condensed matter physics (for-2020)

Popis souboru: application/pdf

Přístupová URL adresa: https://escholarship.org/uc/item/966220w4
https://escholarship.org/content/qt966220w4/qt966220w4.pdf

Deep convolutional autoencoder thermography for artwork defect detection.

Autoři: Liu, Yi Wang, Fumin Liu, Kaixin a další

Zdroj: Quantitative InfraRed Thermography Journal; Nov2024, Vol. 21 Issue 6, p367-383, 17p