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Iteration over Event Space in Time-to-First-Spike Spiking Neural Networks for Twitter (X) Bot Classification Cover

Iteration over Event Space in Time-to-First-Spike Spiking Neural Networks for Twitter (X) Bot Classification

International Journal of Applied Mathematics and Computer Science
Volume 35 (2025): Issue 3 (September 2025)
By: Mateusz Pabian,  Dominik Rzepka and  Mirosław Pawlak  
Open Access
|Sep 2025

Authors

Mateusz Pabian

Department of Measurement and Electronics, AGH University of Krakow, KrakĂłw, Poland

Dominik Rzepka

Department of Measurement and Electronics, AGH University of Krakow, KrakĂłw, Poland

Mirosław Pawlak

Miroslaw.Pawlak@umanitoba.ca

Department of Measurement and Electronics, AGH University of Krakow, KrakĂłw, Poland
Department of Electrical and Computer Engineering, University of Manitoba, Canada
DOI: https://doi.org/10.61822/amcs-2025-0035 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
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Language: English
Page range: 493 - 505
Submitted on: Sep 29, 2024
|
Accepted on: Apr 14, 2025
|
Published on: Sep 8, 2025
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
spiking neural networks,
event-based computing,
bot detection,
supervised learning
Related subjects:
Mathematics,
Applied mathematics

© 2025 Mateusz Pabian, Dominik Rzepka, Mirosław Pawlak, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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