Shaaban A, Chaabouni Z, Strobel M, Furtner W, Weigel R, Lurz F (2024)
Publication Type: Conference contribution
Publication year: 2024
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 53-56
Conference Proceedings Title: 2024 IEEE Radio and Wireless Week, RWW 2024 - 2024 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNeT 2024
Event location: San Antonio, TX, USA
ISBN: 9798350329827
DOI: 10.1109/WiSNeT59910.2024.10438644
This study proposes an approach using spiking resonate-and-fire neurons for hand gesture label refinement, aiming to distinguish the frame in which the hand performs the gesture from background noise. By employing a single layer of only 32 resonate-and-fire neurons directly on time-domain radar data, the approach achieves results comparable to those obtained by methods based on traditional radar preprocessing pipelines, such as fast Fourier transforms, for target detection. Consequently, it has the potential to replace fast Fourier transforms and target detection, enabling the transformation of time-domain data into frequency-dependent spikes in a single step and facilitating further frame-based gesture recognition on sparse, energy-efficient spiking neural networks.
APA:
Shaaban, A., Chaabouni, Z., Strobel, M., Furtner, W., Weigel, R., & Lurz, F. (2024). Resonate-and-Fire Spiking Neurons for Hand Gesture Label Refinement. In 2024 IEEE Radio and Wireless Week, RWW 2024 - 2024 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNeT 2024 (pp. 53-56). San Antonio, TX, USA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Shaaban, Ahmed, et al. "Resonate-and-Fire Spiking Neurons for Hand Gesture Label Refinement." Proceedings of the 2024 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNeT 2024, San Antonio, TX, USA Institute of Electrical and Electronics Engineers Inc., 2024. 53-56.
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