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Related Experiment Video

Updated: Oct 3, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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Combining CNN and Q-learning for increasing the accuracy of lost gamma source finding.

Atefeh Fathi1, S Farhad Masoudi2

  • 1Department of Physics, K.N. Toosi University of Technology, P.O. Box 15875-4416, Tehran, 15418-49611, Iran.

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|February 17, 2022
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This study introduces a novel method combining convolutional neural networks (CNN) and Q-learning to locate and route lost gamma sources in shielded irradiation rooms. The approach significantly enhances accuracy and reduces search time, improving safety in nuclear applications.

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Area of Science:

  • Nuclear Engineering
  • Robotics and Automation
  • Artificial Intelligence

Background:

  • Nuclear technology, particularly gamma sources, is vital in industry and medicine.
  • Locating lost gamma sources in shielded irradiation rooms is a significant safety challenge.
  • Existing methods may be inefficient or inaccurate due to radiation shielding barriers.

Purpose of the Study:

  • To develop an efficient and robust method for simultaneously locating and routing lost gamma sources.
  • To address the challenges posed by radiation blocking barriers in gamma irradiation rooms.
  • To improve the safety and efficiency of operations involving gamma sources.

Main Methods:

  • Utilized a combination of convolutional neural network (CNN) and Q-learning algorithms.
  • Developed a simulated environment using Geant4 for gamma source scenarios.
  • Tested the combined CNN and Q-learning approach in geometries with radiation blocking barriers.

Main Results:

  • Achieved 90% accuracy in locating lost gamma sources.
  • Demonstrated the capability to perform simultaneous locating and routing.
  • The combined method significantly reduced search time and increased accuracy, even with thick barriers.

Conclusions:

  • The integration of CNN and Q-learning offers a powerful solution for lost gamma source retrieval.
  • This hybrid approach overcomes limitations of traditional methods in complex shielded environments.
  • The findings contribute to enhanced safety protocols in nuclear technology applications.