Computer Vision based Auxiliary System for Computer Assembly: System Design and implementation
Master thesis
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http://hdl.handle.net/11250/2618732Utgivelsesdato
2019Metadata
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Sammendrag
This thesis proposes a solution that employs AI in assisting a human withlittle or no technical background for computer assembly in real-time with-out any form of other assistance. To achieve this goal, a state-of-the-artobject detection, namely Lighthead R-CNN is adopted as foundation. Al-terations and modifications of the algorithm are carried out to achieve theoptimal trade-o↵between accuracy loss and speed gain. In more details,it is expected to reduce the complexity of the algorithm in order to makethe solution applicable in a computer with limited computational capacity.Numerical results show that the proposed solution is 5.25% lower in termsof accuracy but almost 8 times faster compared with the competitors. Inaddition to the objective comparisons, we did subjective testing by invitingnon-technical people to assemble di↵erent PCs with assistance of the pro-posed system. The results of the testing show a successful rate of 95.99%.It is worth mentioning that the unsuccessful cases are mainly due to theignorances of the guide or the detector by human beings, rather than erroroutput of the AI based solution.
Beskrivelse
Master's thesis Information- and communication technology IKT590 - University of Agder 2019