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Quantum-Cognitive Tunnelling Neural Networks for Military-Civilian Vehicle Classification and Sentiment Analysis

arXiv 2507.18645 ↗First posted 18 Jul 2025cs.CV cs.AIcited by 0

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Abstract (arXiv)

Prior work has demonstrated that incorporating well-known quantum tunnelling (QT) probability into neural network models effectively captures important nuances of human perception, particularly in the recognition of ambiguous objects and sentiment analysis. In this paper, we employ novel QT-based neural networks and assess their effectiveness in distinguishing customised CIFAR-format images of military and civilian vehicles, as well as sentiment, using a proprietary military-specific vocabulary. We suggest that QT-based models can enhance multimodal AI applications in battlefield scenarios, particularly within human-operated drone warfare contexts, imbuing AI with certain traits of human reasoning.

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References · 13

  1. 2020Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Userscited by 338
  2. 2021Deepfake Detection by Human Crowds, Machines, and Machine-informed Crowdscited by 58
  3. 2019Model-free prediction of spatiotemporal dynamical systems with recurrent neural networks: Role of network spectral radiuscited by 34
  4. 2024Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspectivecited by 9
  5. 2022A Planck Radiation and Quantization Scheme for Human Cognition and Languagecited by 8
  6. 2023Quantum-Inspired Neural Network Model of Optical Illusionscited by 7
  7. 2022Human Perception as a Phenomenon of Quantizationcited by 6
  8. 2024Quantum-tunnelling deep neural network for optical illusion recognitioncited by 6
  9. 2023The Physics of Preference: Unravelling Imprecision of Human Preferences through Magnetisation Dynamicscited by 5
  10. 2024Quantum-Cognitive Neural Networks: Assessing Confidence and Uncertainty with Human Decision-Making Simulationscited by 4
  11. 2023Exploring Cognitive Paradoxes in Video Games: A Quantum Mechanical Perspectivecited by 2
  12. 2024Fake news: No ban, No spread -- with Sequestrationcited by 2
1 more
  1. 2025Quantum Cognition-Inspired EEG-based Recommendation via Graph Neural Networkscited by 1

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