Výsledky vyhľadávania - 3D encoder–decoder architecture*

A novel hybrid layer-based encoder–decoder framework for 3D segmentation in congenital heart disease

Autori: Yaoxi Zhu Hongbo Li Bingxin Cao a ďalší

Zdroj: Sci Rep
Scientific Reports, Vol 15, Iss 1, Pp 1-10 (2025)

Predmety: Heart Defects, Congenital, Science, Deep learning, Heart, Hybrid architectures, Article, Imaging, Three-Dimensional, Deep Learning, 3D CT image, Image Processing, Computer-Assisted, Medicine, Humans, Algorithms, Congenital heart disease, Cardiac segmentation

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40195399
https://doaj.org/article/bf5a61cd628a48edacb57316310c0da4

SISR of Hyperspectral Remote Sensing Imagery Using 3D Encoder-Decoder RUNet Architecture

Autori: Aburaed, Nour Alkhatib, Mohammed Q. Marshall, Stephen a ďalší

Zdroj: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. :1516-1519

Predmety: Electrical engineering. Electronics Nuclear engineering, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Popis súboru: text

ST-3DView: Multi-Scale Contrast-Enhanced 3D Point Cloud Reconstruction of Single-View Objects From Video Scene Transition

Autori: Dipanita Chakraborty Werapon Chiracharit Kosin Chamnongthai

Zdroj: IEEE Access, Vol 13, Pp 69596-69618 (2025)

Predmety: 3D neural network, 3D reconstruction, object segmentation, Electrical engineering. Electronics. Nuclear engineering, scene transition detection, encoder-decoder architecture, point cloud, TK1-9971

Prístupová URL adresa: https://doaj.org/article/9fc22eed249e49a7aa1ba7cd65bced3f

Benchmarking Encoder-Decoder Architectures for Biplanar X-ray to 3D Shape Reconstruction

Autori: Shakya, Mahesh Khanal, Bishesh

Predmety: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing, Machine Learning (cs.LG)

Prístupová URL adresa: http://arxiv.org/abs/2309.13587

Dice Focal Loss with ResNet-like Encoder-Decoder Architecture in 3D Brain Tumor Segmentation

Autori: Hai Nguyen-Truong Quan-Dung Pham

Zdroj: Lecture Notes in Computer Science ISBN: 9783031090011

Encoder-Decoder Architecture for 3D Seismic Inversion

Autori: Gelboim, Maayan Adler, Amir Sun, Yen a ďalší

Témy: Physics - Geophysics, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing, text

URL: http://arxiv.org/abs/2207.14789

Encoder–Decoder Architecture for 3D Seismic Inversion

Autori: Maayan Gelboim Amir Adler Yen Sun a ďalší

Zdroj: Sensors (Basel)
Sensors, Vol 23, Iss 1, p 61 (2022)
Sensors; Volume 23; Issue 1; Pages: 61

Predmety: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, inverse problems, Chemical technology, seismic velocity, deep learning, FOS: Physical sciences, TP1-1185, 02 engineering and technology, transfer learning, seismic inversion, 01 natural sciences, Article, Geophysics (physics.geo-ph), Machine Learning (cs.LG), 0104 chemical sciences, Physics - Geophysics, FOS: Electrical engineering, electronic engineering, information engineering, 3D reconstruction, encoder–decoder, Electrical Engineering and Systems Science - Signal Processing, 0210 nano-technology

Popis súboru: application/pdf

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/36616658
http://arxiv.org/abs/2207.14789
https://doaj.org/article/a47ec4a216ee41f5949792bfa0f45c5f

A novel lightweight 3D CNN for accurate deformation time series retrieval in MT-InSAR

Autori: Mahmoud Abdallah Xiaoli Ding Samaa Younis a ďalší

Zdroj: Science of Remote Sensing, Vol 11, Iss , Pp 100206- (2025)

Predmety: MT-InSAR, Deformation retrieval, Lightweight, 3D encoder-decoder architecture, Separable CNN, Physical geography, GB3-5030, Science

Popis súboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2666017225000124; https://doaj.org/toc/2666-0172

Prístupová URL adresa: https://doaj.org/article/7ce5e628f5fa40d1a5f2babbb8155481

Whole Heart Segmentation Using 3D FM-Pre-ResNet Encoder–Decoder Based Architecture with Variational Autoencoder Regularization

Autori: Marija Habijan Irena Galić Hrvoje Leventić a ďalší

Zdroj: Applied Sciences, Vol 11, Iss 9, p 3912 (2021)

Predmety: artificial intelligence, cardiac CT, cardiac MRI, deep learning, ResNet, variational autoencoder, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Popis súboru: electronic resource

Relation: https://www.mdpi.com/2076-3417/11/9/3912; https://doaj.org/toc/2076-3417

Prístupová URL adresa: https://doaj.org/article/ffa6dc8320a8424e99d6f30ff091b71b

H-Net: A Multitask Architecture for Simultaneous 3D Force Estimation and Stereo Semantic Segmentation in Intracardiac Catheters

Autori: Pedram Fekri Mehrdad Zadeh Javad Dargahi

Zdroj: IEEE Robotics and Automation Letters. 10:844-851

Predmety: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Robotics, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing, Robotics (cs.RO), Machine Learning (cs.LG)

Prístupová URL adresa: http://arxiv.org/abs/2501.00514

Adaptive Feature Medical Segmentation Network: an adaptable deep learning paradigm for high-performance 3D brain lesion segmentation in medical imaging

Autori: Asim Zaman Haseeb Hassan Xueqiang Zeng a ďalší

Zdroj: Front Neurosci
Frontiers in Neuroscience, Vol 18 (2024)

Predmety: 03 medical and health sciences, 0302 clinical medicine, adaptive feature extraction, brain lesion segmentation, computer-aided diagnosis, Neurosciences. Biological psychiatry. Neuropsychiatry, attention mechanism, medical image analysis, encoder-decoder architecture, RC321-571, Neuroscience

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38680446
https://doaj.org/article/25c8d1842e5644808d16dfc43ffba1af

H-Net: A Multitask Architecture for Simultaneous 3D Force Estimation and Stereo Semantic Segmentation in Intracardiac Catheters

Autori: Fekri, Pedram Zadeh, Mehrdad Dargahi, Javad

Témy: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Computer Science - Robotics, text

URL: http://arxiv.org/abs/2501.00514

Leveraging bidirectional long short-term memory in a encoder-decoder architecture to fuse inter-slice information for enhancing burn tissue segmentation using optical coherence tomography.

Autori: Dhiman, Babita Kamboj, Sangeeta Srivastava, Vishal

Zdroj: Biomedical Signal Processing & Control. Sep2025, Vol. 107, pN.PAG-N.PAG. 1p.

Predmety: Long short-term memory, Machine learning, Optical coherence tomography, Surgeons, Deep learning

Multi stage mesh attention UNet architecture for 3D dental segmentation.

Autori: Mouncif, Hamza Kassimi, Amine Gardelle, Thierry Bertin a ďalší

Zdroj: Discover Artificial Intelligence; 11/24/2025, Vol. 5 Issue 1, p1-17, 17p

Predmety: DATA augmentation, DENTISTRY, ORTHODONTICS, ARTIFICIAL neural networks, MORPHOLOGY

DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling

Autori: Ji, Hangyu

Predmety: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing

Prístupová URL adresa: http://arxiv.org/abs/2506.05297

Hierarchical 3D Feature Learning forPancreas Segmentation

Autori: Federica Proietto Salanitri Concetto Spampinato Ulas Bagci a ďalší

Zdroj: Lecture Notes in Computer Science ISBN: 9783030875886

Predmety: Segmentation map, FOS: Computer and information sciences, Computer Science - Machine Learning, Decoding, Convolutional neural network, 02 engineering and technology, 3D modeling, Machine Learning (cs.LG), Medical computing, 03 medical and health sciences, Magnetic resonance imaging, 0302 clinical medicine, Network coding, Statistical tests, Learn+, Machine learning, MRI scan, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Hierarchical encoder-decoder architecture, Encoder-decoder architecture, CT and MRI pancreas segmentation, Image and Video Processing (eess.IV), Feature learning, Fully convolutional neural networks, CT-scan, Electrical Engineering and Systems Science - Image and Video Processing, Computerized tomography, Convolution, Convolutional neural networks, Medical imaging, Fully convolutional neural network

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/36780259
http://arxiv.org/abs/2109.01667
https://link.springer.com/chapter/10.1007/978-3-030-87589-3_25
https://dblp.uni-trier.de/db/journals/corr/corr2109.html#abs-2109-01667

Deep Learning With Noisy Labels for Spatiotemporal Drought Detection

Autori: Cortés-Andrés, Jordi Fernández-Torres, Miguel-Ángel Camps-Valls, Gustau a ďalší

Prispievatelia: Cortés-Andrés, Jordi Fernández-Torres, Miguel-Ángel Camps-Valls, Gustau a ďalší

Zdroj: e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
IEEE Transactions on Geoscience and Remote Sensing

Predmety: Informática, Noise measurement, Drought detection, Data models, Biological system modeling, Convolutional neural networks (CNNS), Droughts, Predictive models, Europe, Label correction (LC), Noisy labels (NLs), Medio Ambiente, Solid modeling, Training, Three-dimensional displays, Spatiotemporal data, Encoder-decoder architecture, Noise, Hydro-climatological data

Popis súboru: application/pdf

Prístupová URL adresa: https://hdl.handle.net/10016/46966

Point Projection Network: A Multi-View-Based Point Completion Network with Encoder-Decoder Architecture

Autori: Weichao Wu Zhong Xie Yongyang Xu a ďalší

Zdroj: Remote Sensing, Vol 13, Iss 23, p 4917 (2021)

Predmety: 3D point clouds, shape completion, deep learning, multi-view-based methods, Science

Popis súboru: electronic resource

Relation: https://www.mdpi.com/2072-4292/13/23/4917; https://doaj.org/toc/2072-4292

Prístupová URL adresa: https://doaj.org/article/58e500052cdc4813bfea607a381de9f5

A Multi-Resolution Attention U-Net for Pavement Distress Segmentation in 3D Images: Architecture and Data-Driven Insights.

Autori: Gong, Haitao Tao, Jueqiang Luo, Xiaohua a ďalší

Zdroj: Mathematics (2227-7390); Sep2025, Vol. 13 Issue 17, p2752, 18p

Predmety: IMAGE segmentation, DEEP learning, SURFACE cracks, THREE-dimensional imaging, DETECTION algorithms, FEATURE extraction

Automatic Evaluation Method for Functional Movement Screening Based on Multi-Scale Lightweight 3D Convolution and an Encoder–Decoder

Autori: Lin, Xiuchun Liu, Yichao Feng, Chen a ďalší

Zdroj: Lin, X, Liu, Y, Feng, C, Chen, Z, Yang, X & Cui, H 2024, 'Automatic Evaluation Method for Functional Movement Screening Based on Multi-Scale Lightweight 3D Convolution and an Encoder–Decoder', Electronics (Switzerland), vol. 13, no. 10, 1813. https://doi.org/10.3390/electronics13101813

Predmety: 3D convolution, automatic evaluation method, encoder–decoder, functional movement screening, human movement feature

Popis súboru: application/pdf

Dostupnosť: https://research.monash.edu/en/publications/35627eab-d5ed-4a3f-bbbe-e5f18d39d46e
https://doi.org/10.3390/electronics13101813
https://researchmgt.monash.edu/ws/files/616959899/599091885-oa.pdf
http://www.scopus.com/inward/record.url?scp=85194265801&partnerID=8YFLogxK