Our new colleague Morris Riedel gave on 7. February 2020 a presentation on Quantum Computing (slides / video) at UTmessan 2020, Icelands biggest IT fair. In addition, the Computer Science Department ran on the public visitor day (8. February 2020) a booth: beside student projects, we showcased research projects, e.g. DEEP-EST.

The DEEP-EST project

For showcasing the machine learning that we do in the DEEP-EST project, we offer a web page that allows you to use the camera of your smartphone (or laptop) to detect objects in real-time. While neural networks are still best trained on a supercomputer, such as DEEP-EST with its Data Analysis Module, the trained neural network even runs in the browser of a smartphone.

Just open the following web page and allow your browser to use the camera: https://nvndr.csb.app/.

(Allow a few seconds for loading the trained model and initialisation.)

The used approach is Single Shot Detector (SSD) (the percentage shows how sure the neural network is about the classification) using the MobileNet neural network architecture. The dataset used for training is COCO (Common Objects in Context), i.e. only objects of the labeled object classes contained in COCO will get detected. The Javascript code that is running in your browser uses Tensorflow Lite and its Object Detection API and model zoo.

If you want learn more about DEEP-EST, have a look at the poster below (click on the picture below for PDF version):