TY - CPAPER
AU - Shah, S. Muhammad Ahmed Hassan
AU - Ullah, Asad
AU - Jan, Sana Ullah
AU - Buchanan, Bill
PY - 2025
DA - August
TI - Transfer Learning-Based Contagious Diseases Transmission Video Surveillance: A COVID-19 Case Study
EP - 467
VL - 1401
DO - https://doi.org/10.1007/978-3-031-91235-1_39
AB - The pervasive transmission of contagious diseases, notably COVID-19, necessitates stringent measures to curb their spread, including SOPs like wearing face masks and maintaining social distancing. This study introduces an innovative system designed to identify individuals in video footage who violate these SOPs. The system operates in phases: detecting individuals in close proximity and identifying those not wearing face masks through facial recognition. Using image processing techniques, it ensures a minimum 2-m separation between individuals via surveillance cameras. The system leverages deep learning to assess SOP compliance, validated on a publicly available face mask detection dataset. This versatile system is applicable to real-time security and surveillance in densely populated environments.
PB - Springer Nature
UR - https://napier-repository.worktribe.com/output/4894299/transfer-learning-based-contagious-diseases-transmission-video-surveillance-a-covid-19-case-study
KW - Coronavirus (COVID-19)
KW - Digital health and technology
ER