Výsledky vyhledávání - convolutional autoencoder(CAE)*

River Channel Microgeomorphic Feature Extraction and Potential Sandstorm Source Identification Method Based on a Convolutional Autoencoder Model

Autoři: Kecong Wu Lirong Chen Yalige Bai a další

Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 2602-2617 (2025)

Témata: convolutional autoencoder (CAE), Ocean engineering, QC801-809, Geophysics. Cosmic physics, microgeomorphic feature, Anomaly values, TC1501-1800, Yarlung Zangbo River, sandstorm sources

Přístupová URL adresa: https://doaj.org/article/94424c5cfbc34885963f0ffe4a93a78c

Detecting Brain Tumor Stages Using Convolutional AutoEncoder (CAE) with Hybrid Deep Learning Method

Autoři: D Agalya S. Kamalakkannan

Zdroj: 2024 2nd International Conference on Sustainable Computing and Smart Systems (ICSCSS). :796-803

An Improved Pan-Sharpening Method Based on Convolutional Autoencoder and Guided Filter (CAE-GF) on Quickbird Images

Autoři: Jessica da Silva Costa Hideo Araki

Zdroj: Anuário do Instituto de Geociências. 47

CAE-ResVGG FusionNet: A Feature Extraction Framework Integrating Convolutional Autoencoders and Transfer Learning for Immature White Blood Cells in Acute Myeloid Leukemia

Autoři: Tusneem Elhassan Ahmed Hamza Osman Mohd Shafry Mohd Rahim a další

Zdroj: Heliyon, Vol 10, Iss 19, Pp e37745- (2024)

Témata: Acute myeloid leukemia, Immature white blood cells, Autoencoder, VGG19, ResNet, Computer-aided diagnosis model, Science (General), Q1-390, Social sciences (General), H1-99

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2405844024137760; https://doaj.org/toc/2405-8440

Přístupová URL adresa: https://doaj.org/article/57a51be9afa9498481b3afe15b315454

Enhanced multiple sclerosis diagnosis by MRI image retrieval using convolutional autoencoders

Autoři: R.M. Haggag Eman M. Ali M.E. Khalifa a další

Zdroj: Egyptian Informatics Journal, Vol 30, Iss , Pp 100698- (2025)

Témata: Multiple sclerosis, Convolutional autoencoder, Content-based medical image retrieval, CBMIR, CAE, MS, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S111086652500091X; https://doaj.org/toc/1110-8665

Přístupová URL adresa: https://doaj.org/article/8aaf2aa32ee4425c8aa7a83d797d3cff

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

Integrasi Convolutional Autoencoder dengan Support Vector Machine untuk Klasifikasi Varietas Almond

Autoři: Rizal Fadlullah Sri Winarno Muhammad Naufal

Zdroj: JuTISI (Jurnal Teknik Informatika dan Sistem Informasi), Vol 11, Iss 1, Pp 63-77 (2025)

Témata: Technology, machine learning, Electronic computers. Computer science, klasifikasi, support vector machine, QA75.5-76.95, varietas almond, convolutional autoencoder

Přístupová URL adresa: https://doaj.org/article/0b190ecfac37461bbde16e0f3ebddf6d

Convolutional Autoencoder Effect on Parallel Magnetic Resonance Imaging.

Autoři: Korti, Amel Bekki, Amène Lalande, Alain

Zdroj: International Journal of Imaging Systems & Technology. Nov2025, Vol. 35 Issue 6, p1-16. 16p.

Témata: *MAGNETIC resonance imaging, *DEEP learning, *IMAGE quality analysis, *AUTOENCODERS, *IMAGE reconstruction

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

Autoři: YuRim Choi Inwhee Joe

Zdroj: Electronics. 13:3946

Computer-Aided Diagnosis of Acute Lymphoblastic Leukemiaby Using a Novel CAE-CNN Framework

Autoři: Mohammed Mansoor Alhammadi

Zdroj: Iraqi Journal for Computers and Informatics, Vol 50, Iss 2, Pp 186-206 (2024)

Témata: Technology, acute lymphoblastic leukemia, convolutional autoencoder, convolutional neural network, feature extraction, computer-aided diagnosis

Přístupová URL adresa: https://doaj.org/article/e9df85c84bfc4fee8a5a49bf1b184bee

Enhancing multi-step-ahead prediction of wave propagation with the CAE-LSTM model: a novel deep learning-based approach to flood dynamics

Autoři: Zheng Han Guanping Long Changli Li a další

Zdroj: Geomatics, Natural Hazards & Risk, Vol 16, Iss 1 (2025)

Témata: Wave propagation, flood dynamics, deep learning, convolutional autoencoders, long short-term memory, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Risk in industry. Risk management, HD61

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1947-5705; https://doaj.org/toc/1947-5713

Přístupová URL adresa: https://doaj.org/article/3e10f6e71d724d5a922f6d9c77ca1330

Robust sensor fault detection in wireless sensor networks using a hybrid conditional generative adversarial networks and convolutional autoencoder

Autoři: Khan, Rehan Saeed, Umer Koo, Insoo a další

Přispěvatelé: Khan, Rehan Saeed, Umer Koo, Insoo a další

Témata: Wireless Sensor Networks (WSNs), Convolutional Autoencoder (CAE), Gramian Angular Field (GAF), Conditional Generative Adversarial Networks (Conditional GANs), sensor faults, Subject Categories::G420 Networks and Communications

Relation: https://ieeexplore.ieee.org/document/10919044; http://hdl.handle.net/10547/626621; IEEE Sensors Journal

Dostupnost: http://hdl.handle.net/10547/626621
https://doi.org/10.1109/JSEN.2025.3547736

Low-dimensional representation and prediction of supersonic gas-solid two-phase flow field based on CAE-BiLSTM

Autoři: Liangliang Zhang Zhixun Xia Likun Ma a další

Zdroj: Results in Engineering, Vol 28, Iss , Pp 107165- (2025)

Témata: Supersonic gas-solid two-phase flow field, Reduced-order model, Flow field prediction, Low-dimensional representation, Convolutional autoencoder, Bidirectional long short-term memory, Technology

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2590123025032207; https://doaj.org/toc/2590-1230

Přístupová URL adresa: https://doaj.org/article/5651201443854389a6ad4ba30df84eac

Unsupervised defect detection for solar photovoltaic cells based on convolutional autoencoder.

Autoři: Zhang, Yufei Zhang, Xu Tu, Dawei

Zdroj: Nondestructive Testing & Evaluation. Dec2025, Vol. 40 Issue 12, p6143-6159. 17p.

Témata: *PHOTOVOLTAIC cells, *ELECTROLUMINESCENCE, *IMAGE segmentation, *ARTIFICIAL neural networks, *OUTLIER detection, *LOSS functions (Statistics)

Canopy Averaged Chlorophyll Content Prediction of Pear Trees Using Convolutional Autoencoder on Hyperspectral Data

Autoři: Subir Paul Vinayaraj Poliyapram Nevrez Imamoglu a další

Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 1426-1437 (2020)

Témata: convolutional autoencoder (CAE), pear orchard, QC801-809, Geophysics. Cosmic physics, 0211 other engineering and technologies, deep learning, 04 agricultural and veterinary sciences, 02 engineering and technology, Canopy averaged chlorophyll content (CACC), Ocean engineering, hyperspectral (HS) data, 0401 agriculture, forestry, and fisheries, Gaussian process regression (GPR), TC1501-1800

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/4609443/8994817/09050560.pdf
https://doaj.org/article/021ee32b52ce425c91b578ef0d36ccb1
https://ieeexplore.ieee.org/document/9050560/
https://ui.adsabs.harvard.edu/abs/2020IJSTA..13.1426P/abstract
http://eprints.iisc.ac.in/65531/
https://doi.org/10.1109/JSTARS.2020.2983000
https://dblp.uni-trier.de/db/journals/staeors/staeors13.html#PaulPIUNK20

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

ECG Identification Algorithm Based on CAE and Improved VGGNet

Autoři: YAN Jie, ZHANG Yefei, ZHANG Xianfei

Zdroj: Jisuanji gongcheng, Vol 51, Iss 1, Pp 295-303 (2025)

Témata: electrocardiogram(ecg), ecg recognition, convolutional autoencoder(cae), residual network(resnet), signal preprocessing, Computer engineering. Computer hardware, TK7885-7895, Computer software, QA76.75-76.765

Popis souboru: electronic resource

Relation: https://www.ecice06.com/fileup/1000-3428/PDF/20250132.pdf; https://doaj.org/toc/1000-3428

Přístupová URL adresa: https://doaj.org/article/77f8130553644b1db92b5a3276a49a8b

CW-CAE: Pulmonary Nodule Detection from Imbalanced Dataset Using Class-Weighted Convolutional Autoencoder

Autoři: Seba Susan Dhaarna Sethi Kriti Arora

Zdroj: Advances in Intelligent Systems and Computing ISBN: 9789811551475

Témata: 3. Good health

Přístupová URL adresa: https://link.springer.com/chapter/10.1007%2F978-981-15-5148-2_71

PSO-MCAE-LCCD: Particle Swarm Optimized MobileNetV2 Convolutional Autoencoder for Lung and Colon Cancer Detection.

Autoři: Kumar, L. K. Suresh Chakravarthy, K. Srinivasa Devi, M. Sathya a další

Zdroj: International Journal of Environmental Sciences (2229-7359); 2025, Vol. 11 Issue 6, p714-722, 9p

Témata: LUNG cancer, COLON cancer, COMPUTER performance, HISTOPATHOLOGY, DEEP learning, CONVOLUTIONAL neural networks, PARTICLE swarm optimization, AUTOENCODERS

Image Enhancement using Hybrid Convolutional Autoencoder with Clahe Post Processing

Autoři: null Pranika null Amandeep

Zdroj: International Journal of Enhanced Research in Management & Computer Applications. 14:59-68