SNM Radiation Signature Classification Using Different Semi-Supervised Machine Learning Models (original) (raw)

Supervised algorithms for particle classification by a transition radiation detector

marialuigia ambriola

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2003

View PDFchevron_right

The Supervised Normalized Cut Method for Detecting, Classifying, and Identifying Special Nuclear Materials

Barak Fishbain

INFORMS Journal on Computing, 2014

View PDFchevron_right

Classification of Sources of Ionizing Radiation in Space Missions: A Machine Learning Approach

Roberto Valerio

View PDFchevron_right

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Alexander Heifetz

2020

View PDFchevron_right

Radionuclide identification analysis using machine learning and GEANT4 simulation

Gina Kusuma

PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NUCLEAR SCIENCE, TECHNOLOGY, AND APPLICATION 2020 (ICONSTA 2020), 2021

View PDFchevron_right

Machine learning for comprehensive nuclear-test-ban treaty monitoring

Ronan Le Bras

CTBTO Spectrum, 2010

View PDFchevron_right

A Partially Supervised Approach for Detection and Classification of Buried Radioactive Metal Targets Using Electromagnetic Induction Data

Anish Turlapaty

IEEE Transactions on Geoscience and Remote Sensing, 2000

View PDFchevron_right

Data Mining in Radiation Portal Monitoring

Tom Burr

2013

View PDFchevron_right

Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty

Kurt Ungar

Journal of Environmental Radioactivity, 2010

View PDFchevron_right

An Instance-based Nearest-neighbor Approach to Classifying Nuclear Explosion Data

Christophe Giraud-Carrier

View PDFchevron_right

A Review on the Application of Machine Learning in Gamma Spectroscopy: Challenges and Opportunities

Nahid Madani

Spectroscopy Journal , 2024

View PDFchevron_right

New Results on Radioactive Mixture Identification and Relative Count Contribution Estimation

CHIMAN KWAN

Sensors

View PDFchevron_right

Machine Learning for Monitoring of Complex Detector Systems

Nevena Ilieva

Zenodo (CERN European Organization for Nuclear Research), 2022

View PDFchevron_right

Applying deep learning for improving image classification in nuclear fusion devices

Ernesto Fabregas

IEEE Access

View PDFchevron_right

Semi-Supervised Classification

Mário Figueiredo

View PDFchevron_right

Signal Discrimination in Thinned Silicon Neutron Detectors using Machine learning

David Cheneler

2019

View PDFchevron_right

Developing a Machine Learning Algorithm-Based Classification Models for the Detection of High-Energy Gamma Particles

Kelvin Kwakye

ArXiv, 2021

View PDFchevron_right

From nuclear track characterization to machine learning based image classification in neutron autoradiography for boron neutron capture therapy

Gisela Saint Martin

PLOS ONE, 2023

View PDFchevron_right

A Novel Collaborative Self-Supervised Learning Method for Radiomic Data

Anca Ralescu

arXiv (Cornell University), 2023

View PDFchevron_right

Signatures for several types of naturally occurring radioactive materials

Kary Myers, Tom Burr

Applied Radiation and Isotopes, 2008

View PDFchevron_right

Pattern Recognition Options to Combine Process Monitoring and Material Accounting Data in Nuclear Safeguards

Co. SEP

View PDFchevron_right

Anomaly detection in gamma ray spectra: A machine learning perspective

Kurt Ungar

2012 IEEE Symposium on Computational Intelligence for Security and Defence Applications, 2012

View PDFchevron_right

Detection of High Energy Materials Using Support Vector Classification

Fernanda Celidonio

Advanced Materials Research, 2012

View PDFchevron_right

Remediating radium contaminated legacy sites: Advances made through machine learning in routine monitoring of “hot” particles

Leslie S Smith

Science of The Total Environment, 2015

View PDFchevron_right

WANDA: AI/ML for Nuclear Data

Vladimir Sobes

2020

View PDFchevron_right

Sensor Management Problems of Nuclear Detection

Minge Xie

Springer Series in Reliability Engineering, 2011

View PDFchevron_right

Noise-Adjusted Principal Component Analysis for Buried Radioactive Target Detection and Classification

Nicolas Younan

IEEE Transactions on Nuclear Science, 2000

View PDFchevron_right

On Semi-Supervised Classification

Mário Figueiredo

2004

View PDFchevron_right

Nuclear spectral analysis via artificial neural networks for waste handling

Sherif Hashem

IEEE Transactions on Nuclear Science, 1995

View PDFchevron_right

Radioxenon Monitoring for Verification of the Comprehensive Nuclear-Test-Ban Treaty

Nitish Srivastava

2010

View PDFchevron_right

Comparison of Supervised Machine Learning Techniques for CERN CMS Offline Data Certification

Valdas Rapsevicius

2018

View PDFchevron_right

A Survey of Semi-Supervised Learning Methods

Nitin Pise

2008 International Conference on Computational Intelligence and Security, 2008

View PDFchevron_right

Semi-Supervised Learning of Gaussian Classifiers

Faysal Başçi

2005

View PDFchevron_right