Spatially Time-Based Robust Tracking and Re-Identification of Kindergarten Students: A Hybrid Deep Learning Framework Combining YOLOv8n and Vision Transformer (ViT)
- DOI
- 10.3390/jimaging12040150
- Published
- 2026-03-30
- Container
- Journal of Imaging
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/jimaging12040150,
title = {Spatially Time-Based Robust Tracking and Re-Identification of Kindergarten Students: A Hybrid Deep Learning Framework Combining YOLOv8n and Vision Transformer (ViT)},
author = {Md. Rahatul Islam and Yui Kataoka and Keisuke Teramoto and Keiichi Horio},
year = {2026},
journal = {Journal of Imaging},
doi = {10.3390/jimaging12040150},
url = {https://doi.org/10.3390/jimaging12040150}
}RIS
TY - JOUR TI - Spatially Time-Based Robust Tracking and Re-Identification of Kindergarten Students: A Hybrid Deep Learning Framework Combining YOLOv8n and Vision Transformer (ViT) AU - Md. Rahatul Islam AU - Yui Kataoka AU - Keisuke Teramoto AU - Keiichi Horio PY - 2026 JO - Journal of Imaging DO - 10.3390/jimaging12040150 UR - https://doi.org/10.3390/jimaging12040150 ER -
APA
Islam, M. R., Kataoka, Y., Teramoto, K., & Horio, K. (2026). Spatially Time-Based Robust Tracking and Re-Identification of Kindergarten Students: A Hybrid Deep Learning Framework Combining YOLOv8n and Vision Transformer (ViT). Journal of Imaging. https://doi.org/10.3390/jimaging12040150
Source records
- crossref · retrieved 2026-09-26T19:08:24.265Z