TY - GEN
T1 - Artirilmiş gerçeklik gözlükleri ile nesne tanima
AU - Albayrak, Mehmet Selcuk
AU - Ner, Alper O.
AU - Ekenel, Hazim Kemal
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Employee training in fast-food restaurants is a long, practice-based process which is mainly done on the job. Employee performance during training directly affects service quality and customer satisfaction. In this study, it is aimed to optimize the training process in fast-food restaurants with use of augmented reality glasses. For this purpose, a comparative study is performed to determine the most suitable model of augmented reality glasses in the market. It is aimed to shorten the training period of the employee, to help the employee in this process and to introduce the objects around him. Light convolutional neural networks are compared to solve the object recognition problem on augmented reality glasses. As a result, MobileNet model is selected and fine-tuned to recognize the objects in a restaurant kitchen. The outcomes of this study will be used to fully train and supervise the employees without the need for a trainer in the future.
AB - Employee training in fast-food restaurants is a long, practice-based process which is mainly done on the job. Employee performance during training directly affects service quality and customer satisfaction. In this study, it is aimed to optimize the training process in fast-food restaurants with use of augmented reality glasses. For this purpose, a comparative study is performed to determine the most suitable model of augmented reality glasses in the market. It is aimed to shorten the training period of the employee, to help the employee in this process and to introduce the objects around him. Light convolutional neural networks are compared to solve the object recognition problem on augmented reality glasses. As a result, MobileNet model is selected and fine-tuned to recognize the objects in a restaurant kitchen. The outcomes of this study will be used to fully train and supervise the employees without the need for a trainer in the future.
KW - Augmented reality glasses
KW - Convolutional neural networks
KW - Deep learning
KW - Fast food employee training
UR - http://www.scopus.com/inward/record.url?scp=85071994178&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071994178&partnerID=8YFLogxK
U2 - 10.1109/SIU.2019.8806255
DO - 10.1109/SIU.2019.8806255
M3 - Conference contribution
AN - SCOPUS:85071994178
T3 - 27th Signal Processing and Communications Applications Conference, SIU 2019
BT - 27th Signal Processing and Communications Applications Conference, SIU 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th Signal Processing and Communications Applications Conference, SIU 2019
Y2 - 24 April 2019 through 26 April 2019
ER -