• Suche: 3D Deep Learning with Python

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101

Novel Deep Learning Model for Predicting Wind Velocity and Power Estimation in Advanced INVELOX Wind Turbines.
Kumar, K. Ramesh ; Selvaraj, M.
Journal of Applied Fluid Mechanics. Jun2023, Vol. 16 Issue 6, p1256-1268. 13p.

Wind speed Wind turbines Wind power Deep learning Wind tunnel testing
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102

AngoraPy: A Python toolkit for modeling anthropomorphic goal-driven sensorimotor systems
Tonio Weidler ; Rainer Goebel ; Mario Senden
Frontiers in Neuroinformatics, Vol 17 (2023)

goal-driven modeling computational modeling deep learning reinforcement learning sensorimotor control cortex …
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103

Estimação Tridimensional da Pose e Forma Humana para Sistemas Autónomos de Telerreabilitação
Varandas, Miguel Ângelo Soares Cerveira

Tele-rehabilitation Machine Learning Three-dimensional human... Parametric model Spinal curvature Telerreabilitação …
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104

Transformación de imágenes 2D en objetos 3D
Arismendi Sánchez, Carlos Eduardo ; Cazorla, Miguel ; Gomez-Donoso, Francisco ; et al.
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)

Imágenes Deep Learning TensorFlow Redes neuronales convolu... OpenCV Ciencia de la Computació... …
Dissertation
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105

Development of anatomically accurate digital organ models for surgical simulation and training.
Kimura, Takashi ; Takiguchi, Kazuaki ; Tsukita, Shigeyuki ; et al.
PLoS ONE; 4/9/2025, Vol. 20 Issue 4, p1-15, 15p

TECHNOLOGICAL innovation... HUMAN anatomy COMPUTER-aided design so... FREEWARE (Computer softw... BLOOD vessels DEEP learning …
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106

SHAFTS (v2022.3): a deep-learning-based Python package for simultaneous extraction of building height and footprint from sentinel imagery
Li, Ruidong ; Sun, Ting ; Tian, Fuqiang ; et al.
Geoscientific Model Development , 16 (2) pp. 751-778. (2023)

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107

kCSD-python, reliable current source density estimation with quality control.
Chintaluri, Chaitanya ; Bejtka, Marta ; Średniawa, Władysław ; et al.
PLoS Computational Biology; 3/14/2024, Vol. 20 Issue 3, p1-23, 23p

DENSITY currents ELECTRIC potential ELECTRIC wire DEEP learning ELECTRIC wiring ELECTRIC fields …
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108

HLA-Clus: HLA class I clustering based on 3D structure.
Shen, Yue ; Parks, Jerry M. ; Smith, Jeremy C.
BMC Bioinformatics. 5/9/2023, Vol. 24 Issue 1, p1-13. 13p.

PEPTIDES HIERARCHICAL clustering... DEEP learning HLA histocompatibility a... STRUCTURAL models K-nearest neighbor class... …
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109

Development of anatomically accurate digital organ models for surgical simulation and training
Takashi Kimura ; Kazuaki Takiguchi ; Shigeyuki Tsukita ; et al.
PLoS One

Models, Anatomic Imaging, Three-Dimension... Deep Learning Lab Protocol Humans Computer Simulation …
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110

MBT3D: Deep learning based multi-object tracker for bumblebee 3D flight path estimation
Luc Stiemer ; Andreas Thoma ; Carsten Braun

Aerospace engineering no... Other information and co... Not Assigned
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111

Investigating the Impact of Two Major Programming Environments on the Accuracy of Deep Learning-Based Glioma Detection from MRI Images
Vadi Su Yilmaz ; Metehan Akdag ; Yaser Dalveren ; et al.
Diagnostics (Basel)
Diagnostics, Vol 13, Iss 4, p 651 (2023)
Diagnostics
Volume 13
Issue 4
Pages: 651

MATLAB Medicine (General) V-Net deep learning 02 engineering and techn... brain tumor detection …
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112

TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning
Pérez-García, F ; Sparks, R ; Ourselin, S
Comput Methods Programs Biomed , 208 , Article 106236. (2021)

Data augmentation Deep learning Medical image computing Preprocessing
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113

Machine learning-based automated segmentation with a feedback loop for 3D synchrotron micro-CT
Shkarin, Roman ; Mikut, R.

ddc:004 machine learning DATA processing & comput... GPU deep learning micro-CT …
Dissertation
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114

A machine learning-based hybrid seismic analysis of a lead rubber bearing isolated building specimen
Yavas, Muhammed Sukru ; Gao, Zheng ; Mekaoui, Nabil ; et al.
In Soil Dynamics and Earthquake Engineering November 2023 174

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115

Considerations on Image Preprocessing Techniques Required by Deep Learning Models. The Case of the Knee MRIs.
BOTNARI, A. ; KADAR, M. ; PATRASCU, J. M.
Maedica - a Journal of Clinical Medicine. 2024, Vol. 19 Issue 3, p526-535. 10p.

MAGNETIC resonance imagi... DEEP learning ORTHOPEDISTS DIAGNOSTIC imaging RESEARCH personnel KNEE injuries
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116

Advancing Vanadium Redox Flow Battery Analysis: A Deep Learning Framework for High-Throughput 3D Visualization and Bubble Quantification via Synchrotron X-ray Tomography
Colliard-Granero, André ; orcid:0000-0002-4615- ; Duan, Kangjun ; et al.

Machine learning Electric batteries Computer vision Deep learning 3D Visualization 3D …
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117

A 3D Synthetic Image Generation Framework: Enabling Deep Learning Feature Detection and Object Classification
Morelli, Antonio ; Di Stefano, Luigi ; Mambelli, Filippo

synthetic data generatio... deep learning data scarcity Datalogic object recognition retail …
Dissertation
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118

Automatic Scan-to-BIM—The Impact of Semantic Segmentation Accuracy
Jidnyasa Patil ; Mohsen Kalantari
Buildings ; Volume 15 ; Issue 7 ; Pages: 1126

semantic segmentation deep learning 3D reconstruction Scan-to-BIM laser scanning BIM
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119

Predicting local control of brain metastases after stereotactic radiotherapy with clinical, radiomics and deep learning features.
Kanakarajan, Hemalatha ; De Baene, Wouter ; Hanssens, Patrick ; et al.
Radiation Oncology. 12/30/2024, Vol. 19 Issue 1, p1-15. 15p.

MACHINE learning RECEIVER operating chara... FEATURE extraction STEREOTACTIC radiotherap... RADIOMICS
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120

On the Value of Using 3D Shape and Electrostatic Similarities in Deep Generative Methods
Bolcato, Giovanni ; Heid, Esther ; Boström, Jonas
Journal of Chemical Information and Modeling. 62(6):1388-1398

Rezension
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