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arXiv · 2407.11013

Quantum-tunnelling deep neural network for optical illusion recognition

Ivan S. Maksymov
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Abstract

The discovery of the quantum tunnelling (QT) effect -- the transmission of particles through a high potential barrier -- was one of the most impressive achievements of quantum mechanics made in the 1920s. Responding to the contemporary challenges, I introduce a deep neural network (DNN) architecture that processes information using the effect of QT. I demonstrate the ability of QT-DNN to recognise optical illusions like a human. Tasking QT-DNN to simulate human perception of the Necker cube and Rubin's vase, I provide arguments in favour of the superiority of QT-based activation functions over the activation functions optimised for modern applications in machine vision, also showing that, at the fundamental level, QT-DNN is closely related to biology-inspired DNNs and models based on the principles of quantum information processing.

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cs.LGcs.AIcs.CVcs.HCcs.NEphysics.soc-phquant-ph

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Ivan S. Maksymov. 2024-06-26. Quantum-tunnelling deep neural network for optical illusion recognition. https://doi.org/10.1063/5.0225771

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