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In: 31st Australian Conference on Human-Computer-Interaction (OZCHI 2019) , pp. 518-522, ACM

Handling Work Complexity with AR/Deep Learning

Hitesh Dhiman , Sebastian Büttner , Carsten Röcker and Raphael Reisch,
Dec 2019

Complexity is a fundamental part of product design and manufacturing today, owing to increased demands for customization and advances in digital design techniques. Assembling and repairing such an enormous variety of components means that workers are cognitively challenged, take longer to search for the relevant information and are prone to making mistakes. Although in recent years deep learning approaches to object recognition have seen rapid advances, the combined potential of deep learning and augmented reality in the industrial domain remains relatively under explored. In this paper we introduce AR-ProMO, a combined hardware/software solution that provides a generalizable assistance system for identifying mistakes during product assembly and repair.

Literature procurement: 31st Australian Conference on Human-Computer-Interaction (OZCHI 2019) , pp. 518-522, ACM
@inproceedings{63,
author= {Dhiman, Hitesh and Büttner, Sebastian and Röcker, Carsten and Reisch, Raphael},
title= {Handling Work Complexity with AR/Deep Learning},
booktitle= {31st Australian Conference on Human-Computer-Interaction (OZCHI 2019) , pp. 518-522},
year= {2019},
editor= {},
volume= {},
series= {},
pages= {4},
address= {Fremantle, WA, Australia},
month= {Dec},
organisation= {},
publisher= {ACM},
note= {},
}