{"abstract":[{"lang":"eng","text":"Spiking Neural Networks (SNNs) have gained significant attention in the field of neuromorphic computing for their potential to mimic the brain’s spiking neurons, allowing event-driven processing based on exact spike timing. In this paper, we introduce a novel architecture that uses the power of SNN in combination with transfer learning to achieve real-time human presence detection and analysis using event-based cameras and compare it with non-event-based cameras. This architecture, which is deployed on edge computing devices, controls a comprehensive pipeline of components, seamlessly integrating various strategies. It combines object detection, transfer learning with SNN, human recognition, localizing and tracking, feature extraction, multi-core architecture, and run-time analysis. The application is initiated by extensively detecting objects and monitoring environments for motion events. Thus, transfer learning adjusts pre-trained Convolutional Neural Network (CNN) weights to SNNs upon detection, enabling event-driven processing. The utilization of multi-core processing speeds up the analytical workload while maintaining real-time operations. The architecture also keeps a valuable spike train dataset, which records important information about recognized objects. This dataset is useful for applications such as behavioral analysis and real-time monitoring."}],"publication":"Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings","year":"2024","editor":[{"last_name":"Iliadis","first_name":"Lazaros","full_name":"Iliadis, Lazaros"},{"full_name":"Maglogiannis, Ilias","last_name":"Maglogiannis","first_name":"Ilias"},{"last_name":"Papaleonidas","first_name":"Antonios","full_name":"Papaleonidas, Antonios"},{"last_name":"Pimenidis","first_name":"Elias","full_name":"Pimenidis, Elias"},{"first_name":"Chrisina","last_name":"Jayne","full_name":"Jayne, Chrisina"}],"type":"conference","user_id":"220548","publication_identifier":{"issn":["1865-0929"],"isbn":["978-3-031-62494-0"],"eisbn":["978-3-031-62495-7"],"eissn":["1865-0937"]},"_id":"4782","author":[{"last_name":"Sanaullah","first_name":"Sanaullah","orcid":"0000-0003-4112-802X","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0003-4112-802X/work/163027382","id":"248865","full_name":"Sanaullah, Sanaullah"},{"first_name":"Shamini","last_name":"Koravuna","full_name":"Koravuna, Shamini"},{"last_name":"Rückert","first_name":"Ulrich","full_name":"Rückert, Ulrich"},{"orcid":"0000-0001-7425-8766","full_name":"Jungeblut, Thorsten","id":"242294","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0001-7425-8766/work/163027383","first_name":"Thorsten","last_name":"Jungeblut"}],"title":"A Spike Vision Approach for Multi-object Detection and Generating Dataset Using Multi-core Architecture on Edge Device","publisher":"Springer Nature Switzerland","conference":{"start_date":"2024-06-27","location":"Corfu, Greece","name":"25th International Conference, EANN 2024","end_date":"2024-06-30"},"series_title":"Communications in Computer and Information Science","status":"public","place":"Cham","page":"317-328","doi":"10.1007/978-3-031-62495-7_24","date_updated":"2024-07-16T10:20:21Z","publication_status":"published","language":[{"iso":"eng"}],"citation":{"apa":"Sanaullah, S., Koravuna, S., Rückert, U., &#38; Jungeblut, T. (2024). A Spike Vision Approach for Multi-object Detection and Generating Dataset Using Multi-core Architecture on Edge Device. In L. Iliadis, I. Maglogiannis, A. Papaleonidas, E. Pimenidis, &#38; C. Jayne (Eds.), <i>Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings</i> (pp. 317–328). Cham: Springer Nature Switzerland. <a href=\"https://doi.org/10.1007/978-3-031-62495-7_24\">https://doi.org/10.1007/978-3-031-62495-7_24</a>","chicago":"Sanaullah, Sanaullah, Shamini Koravuna, Ulrich Rückert, and Thorsten Jungeblut. “A Spike Vision Approach for Multi-Object Detection and Generating Dataset Using Multi-Core Architecture on Edge Device.” In <i>Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings</i>, edited by Lazaros Iliadis, Ilias Maglogiannis, Antonios Papaleonidas, Elias Pimenidis, and Chrisina Jayne, 317–28. Communications in Computer and Information Science. Cham: Springer Nature Switzerland, 2024. <a href=\"https://doi.org/10.1007/978-3-031-62495-7_24\">https://doi.org/10.1007/978-3-031-62495-7_24</a>.","mla":"Sanaullah, Sanaullah, et al. “A Spike Vision Approach for Multi-Object Detection and Generating Dataset Using Multi-Core Architecture on Edge Device.” <i>Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings</i>, edited by Lazaros Iliadis et al., Springer Nature Switzerland, 2024, pp. 317–28, doi:<a href=\"https://doi.org/10.1007/978-3-031-62495-7_24\">10.1007/978-3-031-62495-7_24</a>.","ieee":"S. Sanaullah, S. Koravuna, U. Rückert, and T. Jungeblut, “A Spike Vision Approach for Multi-object Detection and Generating Dataset Using Multi-core Architecture on Edge Device,” in <i>Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings</i>, Corfu, Greece, 2024, pp. 317–328.","bibtex":"@inproceedings{Sanaullah_Koravuna_Rückert_Jungeblut_2024, place={Cham}, series={Communications in Computer and Information Science}, title={A Spike Vision Approach for Multi-object Detection and Generating Dataset Using Multi-core Architecture on Edge Device}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-62495-7_24\">10.1007/978-3-031-62495-7_24</a>}, booktitle={Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings}, publisher={Springer Nature Switzerland}, author={Sanaullah, Sanaullah and Koravuna, Shamini and Rückert, Ulrich and Jungeblut, Thorsten}, editor={Iliadis, Lazaros and Maglogiannis, Ilias and Papaleonidas, Antonios and Pimenidis, Elias and Jayne, ChrisinaEditors}, year={2024}, pages={317–328}, collection={Communications in Computer and Information Science} }","ama":"Sanaullah S, Koravuna S, Rückert U, Jungeblut T. A Spike Vision Approach for Multi-object Detection and Generating Dataset Using Multi-core Architecture on Edge Device. In: Iliadis L, Maglogiannis I, Papaleonidas A, Pimenidis E, Jayne C, eds. <i>Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings</i>. Communications in Computer and Information Science. Cham: Springer Nature Switzerland; 2024:317-328. doi:<a href=\"https://doi.org/10.1007/978-3-031-62495-7_24\">10.1007/978-3-031-62495-7_24</a>","alphadin":"<span style=\"font-variant:small-caps;\">Sanaullah, Sanaullah</span> ; <span style=\"font-variant:small-caps;\">Koravuna, Shamini</span> ; <span style=\"font-variant:small-caps;\">Rückert, Ulrich</span> ; <span style=\"font-variant:small-caps;\">Jungeblut, Thorsten</span>: A Spike Vision Approach for Multi-object Detection and Generating Dataset Using Multi-core Architecture on Edge Device. In: <span style=\"font-variant:small-caps;\">Iliadis, L.</span> ; <span style=\"font-variant:small-caps;\">Maglogiannis, I.</span> ; <span style=\"font-variant:small-caps;\">Papaleonidas, A.</span> ; <span style=\"font-variant:small-caps;\">Pimenidis, E.</span> ; <span style=\"font-variant:small-caps;\">Jayne, C.</span> (Hrsg.): <i>Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings</i>, <i>Communications in Computer and Information Science</i>. Cham : Springer Nature Switzerland, 2024, S. 317–328","short":"S. Sanaullah, S. Koravuna, U. Rückert, T. Jungeblut, in: L. Iliadis, I. Maglogiannis, A. Papaleonidas, E. Pimenidis, C. Jayne (Eds.), Engineering Applications of Neural Networks. 25th International Conference, EANN 2024, Corfu, Greece, June 27–30, 2024, Proceedings, Springer Nature Switzerland, Cham, 2024, pp. 317–328."},"date_created":"2024-07-05T10:09:03Z"}