A Deep Learning Facial Expression
Recognition Based Scoring System For Restaurants
Abstract:
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 AIserver. Both the
food and the environment are supposed to be rated. Currently, three expressions
(satisfied, neutral and disappointed) are provided by the scoring system.
Algorithms:
Haar-AdaBoost
Convolutional Neural Network
(CNN)
SYSTEM CONFIGURATION:
Hardware
requirements:
Processer : Any Update
Processer
Ram : Min 4 GB
Hard Disk : Min 100 GB
Software
requirements:
Operating System : Windows
family
Technology : Python 3.6
IDE : PyCharm
1 comments:
comments
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