Search Results for author: François Drielsma

Found 2 papers, 0 papers with code

Scalable, Proposal-free Instance Segmentation Network for 3D Pixel Clustering and Particle Trajectory Reconstruction in Liquid Argon Time Projection Chambers

no code implementations6 Jul 2020 Dae Heun Koh, Pierre Côte de Soux, Laura Dominé, François Drielsma, Ran Itay, Qing Lin, Kazuhiro Terao, Ka Vang Tsang, Tracy Usher

This work contributes to the development of an end-to-end optimizable full data reconstruction chain for LArTPCs, in particular pixel-based 3D imaging detectors including the near detector of the Deep Underground Neutrino Experiment.

Clustering Instance Segmentation +1

Point Proposal Network for Reconstructing 3D Particle Endpoints with Sub-Pixel Precision in Liquid Argon Time Projection Chambers

no code implementations26 Jun 2020 Laura Dominé, Pierre Côte de Soux, François Drielsma, Dae Heun Koh, Ran Itay, Qing Lin, Kazuhiro Terao, Ka Vang Tsang, Tracy L. Usher

Using as a benchmark the PILArNet public LArTPC data sample in which the voxel resolution is 3mm/voxel, our algorithm successfully predicted 96. 8% and 97. 8% of 3D points within a distance of 3 and 10~voxels from the provided true point locations respectively.

Clustering

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