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Found 5 papers, 1 papers with code
DynoSurf: Neural Deformation-based Temporally Consistent Dynamic Surface Reconstruction
Furthermore, we propose a learnable deformation representation based on the learnable control points and blending weights, which can deform the template surface non-rigidly while maintaining the consistency of the local shape.
Label-free timing analysis of SiPM-based modularized detectors with physics-constrained deep learning
We mathematically demonstrate the existence of the optimal function desired by the method, and give a systematic algorithm for training and calibration of the model.
PulseDL-II: A System-on-Chip Neural Network Accelerator for Timing and Energy Extraction of Nuclear Detector Signals
Recent literature reveals that deep learning models, especially one-dimensional convolutional neural networks, are promising when dealing with digital signals from nuclear detectors.
Sketch2PQ: Freeform Planar Quadrilateral Mesh Design via a Single Sketch
In this work, we present a novel sketch-based system to bridge the concept design and digital modeling of freeform roof-like shapes represented as planar quadrilateral (PQ) meshes.
A Robust Loss for Point Cloud Registration
The performance of surface registration relies heavily on the metric used for the alignment error between the source and target shapes.
