Search Results - Convolutional Autoencoder Model

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

Authors: Kecong Wu Lirong Chen Yalige Bai et al.

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

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

Access URL: https://doaj.org/article/94424c5cfbc34885963f0ffe4a93a78c

Spatially Aware Fusion in 3D Convolutional Autoencoders for Video Anomaly Detection

Authors: Niaz, Asim Ul Amin, Sareer Soomro, Shafiullah et al.

Source: IEEE Access. 12:104770-104784

Subject Terms: Videos, Anomaly detection, Surveillance, Feature extraction, Predictive models, Pedestrians, Optical flow, autoencoders, computer vision, intelligent surveillance systems, three-dimensional convolutional neural network (3DCNN), video-based abnormal event detection, Computer Science, Datavetenskap

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-132046
https://doi.org/10.1109/ACCESS.2024.3435144

Effects of a Multi-Sensor Convolutional Autoencoder Model for Lossy Hyperspectral Data Compression on Surveillance Target Detection

Authors: J. Kuester A. Michel S. Schreiner et al.

Source: 2024 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). :1-5

3D-Hybrid Convolutional Autoencoder Model for Hyperspectral Satellite Data Compression

Authors: Kuester, J. Gross, W. Michel, A. et al.

Source: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. :2564-2567

Subject Terms: ddc:620, Engineering & allied operations

The Model Is the Message: Lightweight Convolutional Autoencoders Applied to Noisy Imaging Data for Planetary Science and Astrobiology

Authors: Caleb Scharf

Source: Icarus.

Subject Terms: Exobiology, Astronomy

Access URL: https://ntrs.nasa.gov/citations/20250004413

Detection of Combustion Instability of Gas Turbine Combustor using Convolutional Autoencoder Model

Authors: Junwoo Jung Daesik Kim Jaemin Beak

Source: Journal of The Korean Society of Combustion. 28:11-19

Convolutional Autoencoder Model for Hyperspectral Multi-Sensor Satellite Data Compression

Authors: Kuester, J. Gross, W. Schreiner, S. et al.

Source: IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. :5383-5386

Subject Terms: ddc:620, Engineering & allied operations

Adaptive Two-Stage Multisensor Convolutional Autoencoder Model for Lossy Compression of Hyperspectral Data

Authors: Jannick Kuester Wolfgang Gross Simon Schreiner et al.

Source: IEEE Transactions on Geoscience and Remote Sensing. 61:1-22

Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy regression

Authors: Afshin Shoeibi Navid Ghassemi Marjane Khodatars et al.

Source: Cognitive Neurodynamics. 17:1501-1523

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, fMRI, CNN-AE, Machine Learning (cs.LG), 3. Good health, 03 medical and health sciences, GWO, 0302 clinical medicine, IT2FR, Diagnosis, Schizophrenia, ADHD

File Description: application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/37974583
http://arxiv.org/abs/2205.15858

AN EXPLAINABLE CONVOLUTIONAL AUTOENCODER MODEL FOR UNSUPERVISED CHANGE DETECTION

Authors: L. Bergamasco Sudipan Saha Lorenzo Bruzzone et al.

Source: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2020, Pp 1513-1519 (2020)

Subject Terms: Technology, Autoencoder, Change Detection, Deep Learning, Explainable Artificial Intelligence, Multi-temporal Analysis, Transfer Learning, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, General Earth and Planetary Sciences, Applied optics. Photonics, 02 engineering and technology, TA1-2040, Engineering (General). Civil engineering (General), Knowmad Institut, General Environmental Science, TA1501-1820

File Description: application/pdf

Access URL: https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/1513/2020/isprs-archives-XLIII-B2-2020-1513-2020.pdf
https://isprs-archives.copernicus.org/articles/XLIII-B2-2020/1513/2020/
https://doaj.org/article/7d42064d3765469cb264daf26fd27c69
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/1513/2020/isprs-archives-XLIII-B2-2020-1513-2020.pdf
https://ui.adsabs.harvard.edu/abs/2020ISPAr43B2.1513B/abstract
https://cris.fbk.eu/handle/11582/323128
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/1513/2020/
https://www.openaccessrepository.it/record/131265

Colour‐patterned fabric defect detection based on an unsupervised multi‐scale U‐shaped denoising convolutional autoencoder model

Authors: Hongwei Zhang Shuting Liu Quanlu Tan et al.

Source: Coloration Technology. 138:522-537

Subject Terms: 01 natural sciences, 0104 chemical sciences

Transferability of Convolutional Autoencoder Model For Lossy Compression to Unknown Hyperspectral Prisma Data

Authors: Küster, Jannick Gross, Wolfgang Schreiner, Simon et al.

Source: 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). :1-5

Subject Terms: ddc:620, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Engineering & allied operations

Large-scale road network partitioning: a deep learning method based on convolutional autoencoder model

Authors: Xu, Pengfei Li, Weifeng Xu, Chenjie et al.

Index Terms: Electrical Engineering and Systems Science - Systems and Control, text

URL: http://arxiv.org/abs/2409.05132

Deep Convolutional Autoencoder Model for Urban Land Use Classification using Mobile Device Data

Authors: Sun, Zhihao Peng, Zhenghiong Yu, Yang et al.

Subject Terms: Urban Land Use Classification, Deep learning, Convolutional Autoencoder Model, Mobile Device Data, Call Detail Records, 11. Sustainability, 15. Life on land

Convolution Autoencoder based Classification Model for Content Based Image Retrieval.

Authors: Rai, Rishi Sisodia, Dilip Singh

Source: Procedia Computer Science. 2025, Vol. 258, p1865-1876. 12p.

Subject Terms: Content-based image retrieval, Convolutional neural networks, Image recognition (Computer vision), Autoencoders, Binary codes, Deep learning

An Inception Convolutional Autoencoder Model for Chinese Healthcare Question Clustering

Authors: Dan Dai Juan Tang Zhiwen Yu et al.

Source: IEEE Transactions on Cybernetics. 51:2019-2031

Subject Terms: China, 0202 electrical engineering, electronic engineering, information engineering, Cluster Analysis, Humans, Diagnosis, Computer-Assisted, Neural Networks, Computer, 02 engineering and technology, Delivery of Health Care, Algorithms

Access URL: https://pubmed.ncbi.nlm.nih.gov/31180903
https://research.polyu.edu.hk/en/publications/an-inception-convolutional-auto-encoder-model-for-chinese-healthc
https://www.ncbi.nlm.nih.gov/pubmed/31180903
https://doi.org/10.1109/TCYB.2019.2916580
https://scholars.cityu.edu.hk/en/publications/an-inception-convolutional-autoencoder-model-for-chinese-healthcare-question-clustering(7e614b06-91f8-4535-9511-dffafc7aa4e0).html
https://ieeexplore.ieee.org/document/8730479/
https://dblp.uni-trier.de/db/journals/tcyb/tcyb51.html#DaiTYWYCHC21

Feature Extraction of QAR Data via Sequence-Parameter Attention Based Convolutional Autoencoder Model

Authors: Qixin Wang Kun Qin Binbin Lu et al.

Source: 2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT). :352-355

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

High performance computing and artificial intelligence algorithms for dimensionality reduction of turbulent flows

Authors: Eiximeno Franch, Benet

Contributors: University/Department: Universitat Politècnica de Catalunya. Departament de Física

Thesis Advisors: Rodríguez Pérez, Ivette María, Lehmkuhl Barba, Oriol

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: reduced order models, high performance computing, deep learning, singular value decomposition, variational autoencoders, Àrees temàtiques de la UPC::Física, Àrees temàtiques de la UPC::Informàtica, 531/534 - Mecànica. Vibracions. Acústica, 004 - Informàtica

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/695826
https://dx.doi.org/10.5821/dissertation-2117-446576

Convolutional Autoencoder Model for Finger-Vein Verification

Authors: Ruqiang Yan Borui Hou

Source: IEEE Transactions on Instrumentation and Measurement. 69:2067-2074

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/8731996
https://dblp.uni-trier.de/db/journals/tim/tim69.html#HouY20
https://doi.org/10.1109/TIM.2019.2921135

Graph convolutional autoencoder model for the shape coding and cognition of buildings in maps

Authors: Xiongfeng Yan Tinghua Ai Min Yang et al.

Source: International Journal of Geographical Information Science. 35:490-512

Subject Terms: 0211 other engineering and technologies, 02 engineering and technology

Access URL: https://jglobal.jst.go.jp/detail?JGLOBAL_ID=202102214460351531
https://doi.org/10.1080/13658816.2020.1768260
https://www.tandfonline.com/doi/full/10.1080/13658816.2020.1768260
https://dblp.uni-trier.de/db/journals/gis/gis35.html#YanAYT21