Nilearn: Statistical Analysis for NeuroImaging in Python — Machine learning for NeuroImaging
Anomaly detection in Skin Model Shapes using machine learning classifiers | SpringerLink
Frontiers | Applications and Challenges of Machine Learning to Enable Realistic Cellular Simulations | Physics
CUBIT – Sandia National Laboratories
Frontiers | Geometric Convolutional Neural Network for Analyzing Surface-Based Neuroimaging Data | Frontiers in Neuroinformatics
MeshingNet: A New Mesh Generation Method based on Deep Learning | DeepAI
Mesh generation - Wikipedia
Voxel and surface mesh (a) and voxel mesh analysis (b). | Download Scientific Diagram
3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification | Scientific Reports
Geometric Computing Lab @ NYU
A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis | Journal of The Royal Society Interface
3D Object Classification | Papers With Code
A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis | Journal of The Royal Society Interface
Infrared spectroscopy data- and physics-driven machine learning for characterizing surface microstructure of complex materials | Nature Communications
Generating 3D Models with PolyGen and PyTorch | by Mason McGough | Towards Data Science
Deep Learning for 3D data with Transformers | Towards Data Science
AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What's the Difference? | IBM
A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis | Journal of The Royal Society Interface
Frontiers | Applications and Challenges of Machine Learning to Enable Realistic Cellular Simulations | Physics