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  4. Vol 8, Issue 3, 2024

A Study on Target Detection and Its Application and Development in the Identification of Unsafe Behaviour of Construction Workers

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DOI: 10.23977/acss.2024.080316 | Downloads: 4 | Views: 83

Author(s)

Tong Zhang 1

Affiliation(s)

1 School of Engineering, China University of Geosciences, Wuhan, China

Corresponding Author

Tong Zhang

ABSTRACT

The construction industry serves as the cornerstone of economic development, but the construction industry is also a very dangerous industry with workplace accidents occurring every year, so automatic identification and recognition of potentially unsafe behaviours and conditions is of great significance in safeguarding the safety of incoming recognised lives. In this paper, firstly, the three major classes of algorithms for target detection are elaborated in detail, the traditional target detection mainly relies on the method of machine learning, the two-phase target detection algorithm based on deep learning is mainly divided into two phases of candidate region production and target detection, while the one-phase target detection algorithm based on deep learning carries out end-to-end target detection without the need to produce a candidate region, and gives an assessment of the performance of the target detection indicators to evaluate the strengths and weaknesses, and summarises and analyses the current applications of target detection in the construction field and the new trends in the future.

KEYWORDS

Target detection, deep learning, evaluation metrics, construction worker safety

CITE THIS PAPER

Tong Zhang, A Study on Target Detection and Its Application and Development in the Identification of Unsafe Behaviour of Construction Workers. Advances in Computer, Signals and Systems (2024) Vol. 8: 112-120. DOI: http://dx.doi.org/10.23977/acss.2024.080316.

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