Výsledky vyhledávání - 3D convolutional autoencoder*

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

Autoři: Niaz, Asim Ul Amin, Sareer Soomro, Shafiullah a další

Zdroj: IEEE Access. 12:104770-104784

Témata: 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

Popis souboru: electronic

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

Enhancing Peer-to-Peer Network Security using 3D Convolutional Autoencoder based Anomaly Detection

Autoři: Rana Veer Samara Sihman Bharattej R Zaid Ajznblasm E. G. Satish a další

Zdroj: 2025 International Conference on Intelligent Systems and Computational Networks (ICISCN). :1-5

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Autoři: Seyfal Sultanov R. A. W. Ayyubi James P. Buban a další

Zdroj: Small. 21

Data‐Driven Detection of Internal Erosion Initiation in Gap‐Graded Soils: Combining Particle‐Scale CFD‐DEM Simulation With 3D Convolutional Autoencoder

Autoři: Jie Qi Negin Yousefpour Guillermo A. Narsilio a další

Zdroj: International Journal for Numerical and Analytical Methods in Geomechanics.

Variational Autoencoder Model Based on 3D Convolutional Neural Network for generative design framework of 3D chair

Autoři: Tae-byeong Park Joung min Park Shokhikha Amalana Murdivien a další

Zdroj: International Journal of Industrial Engineering and Management, Vol 15, Iss 1, Pp 1-17 (2024)

Témata: virtual and augmented reality, Industrial engineering. Management engineering, generative design, variational autoencoder, ai and machine learning, T55.4-60.8, knowledge-based engineering

Přístupová URL adresa: https://doaj.org/article/869add28c59a40139a76f068a94b790d
http://doi.org/10.24867/IJIEM-2024-1-344

Research on 3D convolutional autoencoder enhanced metro abnormal behavior detection based on multi-level attentional memory

Autoři: Run Ye Kun Zhang Cheng Zhang a další

Zdroj: Multimedia Tools and Applications. 84:23861-23879

Deep learning-based automated 3D inspection of helical gears using voxelized CAD models and 3D convolutional autoencoders.

Autoři: Selloum, Rabia Ameddah, Hacene Brioua, Mourad

Zdroj: International Journal of Advanced Manufacturing Technology. Dec2025, Vol. 141 Issue 7/8, p3695-3715. 21p.

Efficient Hyperspectral Data Compression using 3D Convolutional Autoencoder

Autoři: Afsana Afrin Md. Al Mamun

Zdroj: 2024 3rd International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE). :1-5

A 3d convolutional neural network autoencoder for predicting solvent configuration changes in condensed phase biomass reactions

Autoři: Anjana Puliyanda Arul Mozhi Devan Padmanathan Samir H. Mushrif a další

Zdroj: Digital Discovery. 3:1130-1143

Témata: 01 natural sciences, 0104 chemical sciences

Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data

Autoři: Yi Huang Yihui Ren Shinjae Yoo a další

Zdroj: Proceedings of the SC '23 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis. :298-305

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, High Energy Physics - Experiment (hep-ex), Statistics - Machine Learning, 0103 physical sciences, FOS: Physical sciences, Machine Learning (stat.ML), Nuclear Experiment (nucl-ex), Nuclear Experiment, 01 natural sciences, High Energy Physics - Experiment, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2310.15026

Multi-layer convolutional autoencoder for recognizing three-dimensional patterns in attention deficit hyperactivity disorder using resting-state functional magnetic resonance imaging

Autoři: Zarina Begum Kareemulla Shaik

Zdroj: International Journal of Electrical and Computer Engineering (IJECE). 15:3965

Facial Aging Prediction over Time: Integrating Variational Autoencoders (VAEs) with 3D Convolutional Neural Networks (CNNs)

Autoři: Ning Lin Yue Zuo

Zdroj: 2023 International Conference on Applied Physics and Computing (ICAPC). :46-50

Learning Unsupervised Visual Representations using 3D Convolutional Autoencoder with Temporal Contrastive Modeling for Video Retrieval

Autoři: Vidit Kumar Vikas Tripathi Bhaskar Pant

Zdroj: International Journal of Mathematical, Engineering and Management Sciences, Vol 7, Iss 2, Pp 272-287 (2022)

Témata: content-based search, Technology, contrastive learning, QA1-939, 0202 electrical engineering, electronic engineering, information engineering, deep learning, 02 engineering and technology, video retrieval, unsupervised learning, convolutional autoencoder, future prediction, Mathematics

Přístupová URL adresa: https://doaj.org/article/f0ea4cbe295b43d3bac47453f7ed0db2

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

Autoři: Asim Niaz Sareer Ul Amin Shafiullah Soomro a další

Zdroj: IEEE Access, Vol 12, Pp 160315-160316 (2024)

Témata: Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Přístupová URL adresa: https://doaj.org/article/4ae0f9167a834b689b668d30e1e78ff7

The Use of 3D Convolutional Autoencoder in Fault and Fracture Network Characterization

Autoři: Feng Xu Zhiyong Li Bo Wen a další

Zdroj: Geofluids, Vol 2021 (2021)

Témata: QE1-996.5, Geology, 01 natural sciences, 3. Good health, 0105 earth and related environmental sciences

Popis souboru: text/xhtml

Přístupová URL adresa: https://downloads.hindawi.com/journals/geofluids/2021/6650823.pdf
https://doaj.org/article/4d1b193c6ba045a2ae2f0dac472bae54
http://downloads.hindawi.com/journals/geofluids/2021/6650823.pdf
https://downloads.hindawi.com/journals/geofluids/2021/6650823.pdf
https://www.hindawi.com/journals/geofluids/2021/6650823/

Learning Spatiotemporal Features for Movie Scene Retrieval Using a 3D Convolutional Autoencoder

Autoři: Vidit Kumar Vikas Tripathi Bhaskar Pant

Zdroj: Computational Intelligence in Analytics and Information Systems ISBN: 9781003332312

Revealing Patterns of Symptomatology in Parkinson's Disease: A Latent Space Analysis with 3D Convolutional Autoencoders

Autoři: Martínez-Murcia, Francisco Jesús

Multi-layer convolutional autoencoder for recognizing three-dimensional patterns in attention deficit hyperactivity disorder using resting-state functional magnetic resonance imaging.

Autoři: Begum, Zarina Shaik, Kareemulla

Zdroj: International Journal of Electrical & Computer Engineering (2088-8708); Aug2025, Vol. 15 Issue 4, p3965-3976, 12p

Témata: ATTENTION-deficit hyperactivity disorder, FUNCTIONAL magnetic resonance imaging, SPATIO-temporal variation, DEEP learning, COGNITIVE science, CONVOLUTIONAL neural networks, MACHINE learning

Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data

Autoři: Huang, Yi Ren, Yihui Yoo, Shinjae a další

Témata: Statistics - Machine Learning, Computer Science - Machine Learning, High Energy Physics - Experiment, Nuclear Experiment, text

URL: http://arxiv.org/abs/2310.15026

Spatial–Spectral Joint Hyperspectral Anomaly Detection Based on a Two-Branch 3D Convolutional Autoencoder and Spatial Filtering

Autoři: Shuai Lv Siwei Zhao Dandan Li a další

Zdroj: Remote Sensing, Vol 15, Iss 10, p 2542 (2023)

Témata: hyperspectral image, anomaly detection, 3D convolutional autoencoder, spatial–spectral joint information, spatial filtering, Science

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2072-4292/15/10/2542; https://doaj.org/toc/2072-4292

Přístupová URL adresa: https://doaj.org/article/5fe2e6f1e37d4e21a18d268e1067c8f9