Fast Person Detection Using YOLOX With AI Accelerator For Train Station Safety
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866908827580891136 |
|---|---|
| author | Achmadiah, Mas Nurul Setyawan, Novendra Bryantono, Achmad Arif Sun, Chi-Chia Kuo, Wen-Kai |
| author_facet | Achmadiah, Mas Nurul Setyawan, Novendra Bryantono, Achmad Arif Sun, Chi-Chia Kuo, Wen-Kai |
| contents | Recently, Image processing has advanced Faster and applied in many fields, including health, industry, and transportation. In the transportation sector, object detection is widely used to improve security, for example, in traffic security and passenger crossings at train stations. Some accidents occur in the train crossing area at the station, like passengers uncarefully when passing through the yellow line. So further security needs to be developed. Additional technology is required to reduce the number of accidents. This paper focuses on passenger detection applications at train stations using YOLOX and Edge AI Accelerator hardware. the performance of the AI accelerator will be compared with Jetson Orin Nano. The experimental results show that the Hailo-8 AI hardware accelerator has higher accuracy than Jetson Orin Nano (improvement of over 12%) and has lower latency than Jetson Orin Nano (reduced 20 ms). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_10593 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Fast Person Detection Using YOLOX With AI Accelerator For Train Station Safety Achmadiah, Mas Nurul Setyawan, Novendra Bryantono, Achmad Arif Sun, Chi-Chia Kuo, Wen-Kai Computer Vision and Pattern Recognition Recently, Image processing has advanced Faster and applied in many fields, including health, industry, and transportation. In the transportation sector, object detection is widely used to improve security, for example, in traffic security and passenger crossings at train stations. Some accidents occur in the train crossing area at the station, like passengers uncarefully when passing through the yellow line. So further security needs to be developed. Additional technology is required to reduce the number of accidents. This paper focuses on passenger detection applications at train stations using YOLOX and Edge AI Accelerator hardware. the performance of the AI accelerator will be compared with Jetson Orin Nano. The experimental results show that the Hailo-8 AI hardware accelerator has higher accuracy than Jetson Orin Nano (improvement of over 12%) and has lower latency than Jetson Orin Nano (reduced 20 ms). |
| title | Fast Person Detection Using YOLOX With AI Accelerator For Train Station Safety |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2602.10593 |