English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper proposed a method to realize inclination measurement for the industrial Internet of Things (IIoT) assembly platform by utilizing deep learning technology. Because the existence of inclination angle of platform will introduce slight damages to the products during the assembly process, our research group designed a system to tackle this problem by replacing the motion estimation algorithm with a classification mechanism. In other words, by classifying the image of the installation platform, it is capable to determine which inclination angle (image class) an input image belongs to. From the analysis of evaluation experiments, the proposed system for inclination measurement mechanism is proved effective when tackling the problems mentioned above. In addition, the proposed IoT system costs less computation power and achieves relatively higher measurement accuracy.

Feature Classification-Based Inclination Measurement for Industrial Assembly Platform