Emotion Recognition System for ATM
Check our case study on how we had developed a model which recognizes emotions with 97% accuracy and aims to improve the services
- Manufacturing / Fintech
- 14 months
- Machine Learning, Deep Learning, Computer Vision, Emotional Analysis, Hardware
To be honest, there was no problem as such. But today the ocean of competition in services is no longer even red but already crimson, so one of the main tasks of any business is to improve its services in all available ways.
That’s why we started cooperating with one bank, whose name is under NDA, which wanted to evaluate its services using Computer Vision. We have to tell that this project in the Security Systems field has become one of the most fascinating and interesting that we’ve ever participated in.
The goal was to teach cash dispensers to recognize people’s emotions when using the device assessing the quality of the services provided. This was possible thanks to Computer Vision technologies, so we began to generate ideas and select the most viable. See what we got.
+21% Overall customer satisfaction
87% customers leave review using AI
+11% Increase in revenue
The model we developed recognizes emotions with 97% accuracy according to our tests. This enables our customer to estimate whether their services make the users feel pleased.
Our soft had just been integrated so we do not have any facts on how the bank improved its services but we will immediately update as soon as we receive this data.
Texts haven’t uploaded yet, but you can see some UI/UX.
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