Graph Neural Networks for Radiological/Nuclear Detection with Static Detector Networks-Reference-Cited by-同舟云学术

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Graph Neural Networks for Radiological/Nuclear Detection with Static Detector Networks

Published:2023-11-04 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)
language:
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Author:

Verlie M. D.¹,Murnane D. T.²,Butko A.²,Cooper R.³,Kiran M.²,Rofors E.³,Vetter K.¹

Affiliation:

1. University of California, Berkeley,Department of Nuclear Engineering,Berkeley,California,United Statesof America

2. Lawrence Berkeley National Laboratory (LBNL),Computational Research Division,Berkeley,California,United States of America

3. Lawrence Berkeley National Laboratory (LBNL),Applied Nuclear Physics Program,Berkeley,California,United States of America

Funder

U.S. Department of Energy

Advanced Scientific Computing Research

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10337770/10337807/10338743.pdf?arnumber=10338743

Reference5 articles.

1. Non-negative Matrix Factorization of Gamma-Ray Spectra for Background Modeling, Detection, and Source Identification

2. A Comprehensive Survey on Graph Neural Networks

3. Graph neural networks in particle physics

4. Interaction networks for learningabout objects, relations and physics;Battaglia,2016

5. Directional message passing for molecular graphs;Gasteiger

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