Original paper
Vehicle weight identification system for spatiotemporal load distribution on bridges based on non-contact machine vision technology and deep learning algorithms
Abstract
Accurate information regarding the weight of vehicle loads plays a significant role in maintaining the structural health of bridges. However, the only method currently available for ascertaining the weight of loads is the bridge weigh-in-motion (BWIM) system, which is not widely used because of the high cost of the large device involved. There is therefore a need to develop an effective, low-cost technology to ascertain vehicle loads in relation...
Paper Details
Title
Vehicle weight identification system for spatiotemporal load distribution on bridges based on non-contact machine vision technology and deep learning algorithms
Published Date
Jul 1, 2020
Journal
Volume
159
Pages
107801 - 107801
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