hrvatski jezikClear Cookie - decide language by browser settings

Integrating tagged neutron inspection with explainable AI for threat material identification

Shahabinejad, Hadi; Sudac, Davorin; Nađ, Karlo; Espagnon, Isabelle; Sainte Foy, Clotilde de; Perot, Bertrand; Carasco, Cedric; Sardet, Alix; Friedmann, Edwin; Poli, Jean Philippe; Delgado, Jessica; Pino, Felix; Moretto, Sandra; Mer, Christine; Sannie, Guillaume; Obhođaš, Jasmina (2026) Integrating tagged neutron inspection with explainable AI for threat material identification. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1081 . ISSN 0168-9002

[img] PDF - Accepted Version - article
Restricted to Closed Access until January 2028.
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (4MB) | Request a personal copy from author

Abstract

Here we present an innovative approach for detecting threat materials within a sealed container by integrating tagged fast neutron activation analysis with Explainable Artificial Intelligence (XAI). Two AI models, a FeedForward Neural Network (FFNN) and a Convolutional Neural Network (CNN), were developed to analyze the emitted gamma rays to identify materials like explosives and drugs based on depth profiles of carbon, nitrogen, and oxygen concentrations. XAI was applied to make the models' decision-making process transparent. The method is adaptable to various spectrometric analyses. We demonstrate its effectiveness using data obtained by the Rapidly Relocatable Tagged Neutron Inspection System (RRTNIS), which is a complementary sensor to X-ray radiography for inspecting cargo containers, despite challenges such as variable material placement, background noise, and shielding effects. Our approach successfully locates and categorizes threat materials, both alone and within surrounding materials, at various locations within sealed cargo containers.

Item Type: Article
Uncontrolled Keywords: threat material identification; neutron activation; spectrum analysis; deep learning; eXplainable artificial intelligence (XAI); rapidly relocatable tagged neutron inspection system (RRTNIS)
Subjects: NATURAL SCIENCES
NATURAL SCIENCES > Physics
Divisions: Division of Experimental Physics
Projects:
Project titleProject leaderProject codeProject type
EfficieNT Risk-bAsed iNspection of freight Crossing bordErs without disrupting business-ENTRANCEJasmina Obhođaš883424EK
Underwater SecurityJasmina Obhođaš101121288EK
Depositing User: Virna Brumnić
Date Deposited: 17 Apr 2026 09:28
URI: http://fulir.irb.hr/id/eprint/11749
DOI: 10.1016/j.nima.2025.170921

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

Contrast
Increase Font
Decrease Font
Dyslexic Font
Accessibility