Ultra-Low Power Neuromorphic Obstacle Detection Using a Two-Dimensional Materials-Based Subthreshold...
Ultra-Low Power Neuromorphic Obstacle Detection Using a Two-Dimensional Materials-Based Subthreshold Transistor
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Contents
Accurate, timely and selective detection of moving obstacles is crucial for reliable collision avoidance in autonomous robots. The area- and energy-inefficiency of CMOS-based spiking neurons for obstacle detection can be addressed through the reconfigurable, tunable and low-power operation capabilities of emerging two-dimensional (2D) materials-bas...
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Full title
Ultra-Low Power Neuromorphic Obstacle Detection Using a Two-Dimensional Materials-Based Subthreshold Transistor
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TN_cdi_proquest_journals_2774003899
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2774003899
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E-ISSN
2331-8422
DOI
10.48550/arxiv.2302.02095
