This project is the startup idea of three serial entrepreneurs who want to automate the payment process in canteens. The product can be described as follows: The guest moves his tray under the camera. Our system scans the items on the tray and automatically
recognizes and quantifies the products in real time. The names of the products, along with their prices, are then displayed on our dashboard. This enables the system to calculate the total price for the customer, who can then start the checkout process and pay for his products.
Challenge: The system should be able to learn the detection of new products only with a few images (e.g. "continous-learning"). Usually, at least a few hundred images are required to train a neural network to detect a new item and training AI systems with only a few images is still an open research field. Because of that, not many engineers are able to build sufficient systems, which is the reason why this part of the project was the biggest challenge.
This specific feature is needed because a canteen offers new dishes every day. Because of that, there is only a limited amount of time and limited data available to train the object detection system on these new dishes.
Through our experience in building AI systems, we where able to solve the "continous-learning" challenge and deliver an accurate and robust object detection system, together with a responsive web-dashboard to visualize the results.