Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/6527
Title: Computer vision and hybrid reality for construction safety risks: A pilot study
Authors: Prof. LI Yi Man, Rita 
Leung, Tat Ho 
Issue Date: 2019
Source: In Yang, X.S., Sherratt, S., Dey, N. & Joshi, A. (eds.) (2019). Fourth international congress on information and communication technology (pp. 17-22).
Conference: 4th International Congress on Information and Communication Technology 
Abstract: Construction sites are among the most hazardous venues. While most of the previous research has shed light on the human aspect, we propose to utilise the fast R-CNN object detection method to detect the construction hazard on sites and employ mixed reality to enable the artificial intelligence to detect the hazard. Fast region-based convolutional neural network object detection acquires expert knowledge to identify objects in the image. Unlike image classification, the complexity of object detection always implies an increase in complexity which demands solutions with regard to speed, accuracy and simplicity.
Type: Conference Paper
URI: http://hdl.handle.net/20.500.11861/6527
ISBN: 9789813293427
9789813293434
DOI: 10.1007/978-981-32-9343-4_2
Appears in Collections:Economics and Finance - Publication

Show full item record

SCOPUSTM   
Citations

7
checked on Nov 17, 2024

Page view(s)

123
Last Week
1
Last month
checked on Nov 21, 2024

Google ScholarTM

Impact Indices

Altmetric

PlumX

Metrics


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.