Multiple Object Detection Architecture-based Comparative Performance for Safe Construction Scenario

Abstract

Artificial intelligence has access to every field in this era. Currently, you have access to everything, from simple tasks to quick calculations. The construction industry is one of them. Safety work, installation, and construction are also part of the drive. Demonstrating the pipeline to date does not prepare as comprehensive an assessment as it could. To this end, we benchmark performance using several cutting-edge approaches that have recently the best performance from state-of-the-art method studies, such as YOLOv5x, YOLOv6l, YOLOv7x, and YOLOv8x. The result show that the recent YOLOv8x accomplish the most effective at generating region of interest box comprehensively. Whereas some existing approaches, like YOLOv5x and v7x, get the highest capacity at classification instead.