Domain-adaptive faster R-CNN for non-PPE identification on construction sites from body-worn and general images

Ensuring consistent compliance with Personal Protective Equipment (PPE) requirements on construction sites is crucial for worker safety. Although deep learning-based methods already perform well in detecting non-PPE cases, there is still scope to further improve accuracy. Progress is hindered by the difficulty of building representative datasets: strict regulations mandate PPE usage, so genuine non-PPE instances are rare, even though such examples are essential for training robust detectors. To address this challenge, this study develops a Domain Adaptation (DA)-based Faster Region-Based Convolutional Neural Network (Faster R-CNN) for detecting five non-PPE categories: "Non-helmet", "Non-mask", "Non-glove",…