TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Chang, Wan-Jung
A1  - Schmelzer, Miriam
A1  - Kopp, Florian
A1  - Hsu, Chia-Hao
A1  - Su, Jian-Ping
A1  - Chen, Liang-Bi
A1  - Chen, Ming-Che
T1  - A Deep Learning Facial Expression Recognition based Scoring System for Restaurants
T2  - International Conference on Artificial Intelligence in Information and Communication (ICAIIC), 11-13 February 2019, Okinawa, Japan
N2  - Recently, the popularity of automated and unmanned restaurants has increased. Due to the absence of staff, there is no direct perception of the customers' impressions in order to find out what their experiences with the restaurant concept are like. For this purpose, this paper presents a rating system based on facial expression recognition with pre-trained convolutional neural network (CNN) models. It is composed of an Android mobile application, a web server, and a pre-trained AI-server. Both the food and the environment are supposed to be rated. Currently, three expressions (satisfied, neutral and disappointed) are provided by the scoring system.
KW  - Automated Restaurants
KW  - Deep Learning
KW  - Facial Recognition
KW  - Restaurant Scoring
KW  - Unmanned Restaurant
KW  - Internet of Things
KW  - IoT
Y1  - 2019
SN  - 978-1-5386-7822-0
SB  - 978-1-5386-7822-0
SN  - 978-1-5386-7823-7
SB  - 978-1-5386-7823-7
U6  - https://doi.org/10.1109/ICAIIC.2019.8668998
DO  - https://doi.org/10.1109/ICAIIC.2019.8668998
SP  - 4
S1  - 4
PB  - IEEE
ER  -