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3D Large Kernel Anisotropic Network for Brain Tumor Segmentation | SpringerLink
OSA | Single-photon computational 3D imaging at 45 km
Fast and Accurate Electron Microscopy Image Registration with 3D Convolution | SpringerLink
Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction - ScienceDirect
OpenGL - Wikipedia
Rapid near-atomic resolution single-particle 3D reconstruction with SIMPLE - ScienceDirect
3D Gravity Modeling of Complex Salt Features in the Southern Gulf of Mexico
Review: deep learning on 3D point clouds
PDF) Deep Learning Advances on Different 3D Data Representations: A Survey
A Level-Set Approach to 3D Reconstruction From Range Data
Programming Guide :: CUDA Toolkit Documentation
3D spatially-adaptive canonical correlation analysis: Local and global methods - ScienceDirect
Multi-input stochastic prediction of insulin sensitivity for tight glycaemic control using insulin sensitivity and blood glucose data - ScienceDirect
Real-time visualization of 3D terrains and subsurface geological structures - ScienceDirect
PDF) A 3D-CNN and LSTM based Multi-task Learning Architecture for Action Recognition
Calorimetry with deep learning: particle simulation and reconstruction for collider physics | SpringerLink
RDI – 3D asfaltové SBS pásy pro šikmé střechy | Budujte.cz
Sensors | Free Full-Text | Deep Learning on Point Clouds and Its Application: A Survey | HTML
Modelová anaerobní kofermentace hovězí kejdy s bioodpady z výroby ...
High Resolution Tomographic Analysis of in vitro 3D Glioblastoma Tumor Model under Long-Term Drug Treatment | bioRxiv
AI Technology to Innovate Diagnostic Imaging : Hitachi Review
3D GeoDesign | geovap.cz
Dyndrite Enters 3D Printing with Their Own Geometry Kernel > ENGINEERING.com
A remote EPID-based dosimetric TPS-planned audit of centers for clinical trials: outcomes and analysis of contributing factors | Radiation Oncology | Full Text
Mineral design 3D prejza červená - asfaltový izolační pás s posypem
Efficient 3D Depthwise and Separable Convolutions with Dilation for Brain Tumor Segmentation | SpringerLink