Výsledky vyhledávání - 3D Conventional Autoencoder*

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.

Témata: *HELICAL gears, *ENGINEERING inspection, *INSPECTION & review, *THREE-dimensional modeling, *INDUSTRIAL applications, *INDUSTRIAL robots, *DEEP learning

Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders

Autoři: Muhammad Sajid Kaleem Razzaq Malik Ateeq Ur Rehman a další

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-18 (2025)

Témata: 2D, Vision Transformers, 3D, Masked Autoencoders, 2D Semantics, Medicine, Science

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2045-2322

Přístupová URL adresa: https://doaj.org/article/3143c9ff3a0846e5bbefb25e2bfc10b7

An Advanced Immersion Level Prediction Using Ensemble Classifier with Heuristic Search Algorithm in 3D Games Content Generated Virtual Environments.

Autoři: Sundararajan, Kamalanathan Santhanam, Prasanna

Zdroj: Fusion: Practice & Applications; 2026, Vol. 21 Issue 1, p277-292, 16p

Témata: ARTIFICIAL intelligence, METAHEURISTIC algorithms, LONG short-term memory, AUTOENCODERS, HEURISTIC

Sense Less, Generate More: Pre-training LiDAR Perception with Masked Autoencoders for Ultra-Efficient 3D Sensing

Autoři: Tayebati, Sina Tulabandhula, Theja Trivedi, Amit R.

Témata: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2406.07833

Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders.

Autoři: Sajid, Muhammad Razzaq Malik, Kaleem Ur Rehman, Ateeq a další

Zdroj: Scientific Reports; 1/25/2025, Vol. 15 Issue 1, p1-18, 18p

Témata: NATURAL language processing, ARTIFICIAL intelligence, TRANSFORMER models, COGNITIVE psychology, ELECTRONIC data processing

Recovering hidden degrees of freedom using Gaussian processes.

Autoři: Diez, Georg Dethloff, Nele Stock, Gerhard

Zdroj: Journal of Chemical Physics. 9/28/2025, Vol. 163 Issue 12, p1-11. 11p.

Témata: *MOLECULAR dynamics, *AUTOENCODERS, *GAUSSIAN distribution, *STATISTICAL correlation, *PHYSICS

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

3D variational autoencoder for fingerprinting microstructure volume elements

Autoři: Michael D. White Michael D. Atkinson Adam J. Plowman a další

Zdroj: Computational Materials Science. 259:114145

Témata: Machine Learning, FOS: Computer and information sciences, Materials Science, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2503.17427

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

Three-dimensional semi-supervised lumbar vertebrae region of interest segmentation based on MAE pre-training.

Autoři: Liu, Yang Chen, Jian Hai, Jinjin a další

Zdroj: Journal of X-Ray Science & Technology; Jan2025, Vol. 33 Issue 1, p270-282, 13p

Témata: SUPERVISED learning, LUMBAR vertebrae, IMAGE segmentation, LUMBOSACRAL region, AUTOENCODERS

Optimizing 3D printing through enhancements in inverse autoencoder models and guided decoders for predicting mechanical properties.

Autoři: Nguyen, Phuong Dong Hoang, Tien-Dat Nguyen, Thanh Q.

Zdroj: Progress in Additive Manufacturing; Oct2025, Vol. 10 Issue 10, p8729-8750, 22p

A combination method of stacked autoencoder and 3D deep residual network for hyperspectral image classification

Autoři: Jinling Zhao Lei Hu Yingying Dong a další

Zdroj: International Journal of Applied Earth Observations and Geoinformation, Vol 102, Iss , Pp 102459- (2021)

Témata: Deep learning, Hyperspectral remote sensing, Residual network, 3D convolutional neural network, Spectral-spatial features, Stacked autoencoder, Physical geography, GB3-5030, Environmental sciences, GE1-350

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S0303243421001665; https://doaj.org/toc/1569-8432

Přístupová URL adresa: https://doaj.org/article/4549b09e51ee4d4cbd419b3cbe97ef77

Hybrid 3D Medical Image Segmentation Using CNN and Frequency Transformer Fusion.

Autoři: Labbihi, Ismayl El Meslouhi, Othmane Elassad, Zouhair Elamrani Abou a další

Zdroj: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ); Aug2025, Vol. 50 Issue 15, p11713-11726, 14p

Témata: CONVOLUTIONAL neural networks, TRANSFORMER models, FAST Fourier transforms, COMPUTER-assisted image analysis (Medicine), AUTOENCODERS, FOURIER transforms, ARTIFICIAL neural networks

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

DAR-MDE: Depth-Attention Refinement for Multi-Scale Monocular Depth Estimation.

Autoři: Abdulwahab, Saddam Rashwan, Hatem A. El-Melegy, Moumen T. a další

Zdroj: Journal of Sensor & Actuator Networks; Oct2025, Vol. 14 Issue 5, p90, 28p

Témata: AUTOENCODERS, DEPTH maps (Digital image processing), THREE-dimensional imaging, REAL-time computing

Detection, quantification, malignancy prediction and growth forecasting of pulmonary nodules using deep learning in follow-up CT scans

Autoři: Rafael-Palou, Xavier

Přispěvatelé: University/Department: Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions

Thesis Advisors: González Ballester, Miguel Ángel, Piella Fenoy, Gemma, Ribas Ripoll, Vicent Jordi

Zdroj: TDX (Tesis Doctorals en Xarxa)

Témata: Lung cancer prediction, Nodule detection, Nodule segmentation, Nodule characterization, Nodule malignancy estimation, Nodule follow-up, Nodule re-identification, Nodule growth forecasting, Uncertainty modelling and quantification, Convolutional neural networks, Variational autoencoders, Siamese neural networks, Generative networks, Transfer learning, Computer vision, Deep learning, Machine learning, Predicció del càncer de pulmó, Detecció de nòduls, Segmentació de nòduls, Caracterització de nòduls, Predicció de malignitat de nòduls, Seguiment de nòduls, Re-identificació de nòduls, Creixement de nòduls, Modelatge i quantificació de la malignitat, Xarxes neuronals convolucionals, Autoencoders variacional, Xarxes neuronals siameses, Xarxes generatives, Aprenentatge per transferència, Pipelines, Visió per computador, Aprenentatge profund, Aprenentatge automàtic

Popis souboru: application/pdf

Přístupová URL adresa: http://hdl.handle.net/10803/672964

Efficient Data Compression for 3D Sparse TPC via Bicephalous Convolutional Autoencoder

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

Témata: Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/2111.05423

TVAE-3D: Efficient multi-view 3D shape reconstruction with diffusion models and transformer based VAE.

Autoři: Sajid, Muhammad Malik, Kaleem Razzaq Khan, Ali Haider a další

Zdroj: Cluster Computing; Nov2025, Vol. 28 Issue 13, p1-22, 22p

Témata: COMPUTER vision, THREE-dimensional imaging, PROBABILISTIC generative models, TRANSFORMER models, POINT cloud, LATENT variables

Diffusion models for topology optimization in 3D printing applications.

Autoři: Bekbolat, Amanali Kurokawa, Syuhei Kamaru Zaman, Fadhlan Hafizhelmi a další

Zdroj: Journal of Applied Physics; 4/7/2025, Vol. 137 Issue 13, p1-16, 16p

Témata: GENERATIVE adversarial networks, ENGINEERING design, ENGINEERING models, AEROSPACE engineers, CIVIL engineering

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/