Kasper Hall and Noell Hall defended their Master thesis in MPCAS at the Chalmers University of Technology on 10 June 2022 at 14:00. Congrats!
Title: Interference Object Detection using TensorFlow Lite and Transfer Learning for Android Devices
With the rapid evolution of machine learning and artificial intelligence faster and more robust network architectures are developed. This is possible due to the increase in computational power, improved algorithms and the creation of large scale annotated datasets. Re-purposing these state of the art networks using transfer learning allows for customized models to be created and applied to niche problems. In this paper, we create an object detection application able to detect interference points in anechoic testing chambers. The application runs detection on a mobile device using networks created with TensorFlow Lite. Utilizing the detection result the application can give advice on how to improve the installation in the testing chamber and can thus enforce a baseline for how installations are conducted increasing the repeatability of tests.
Name of the master programme: MPCAS – Complex Adaptive Systems
Examiner: Giovanni Volpe
Supervisor: Giovanni Volpe and Christian Heina, Ericsson
Opponent: Angelo Barona Balda
Place: Origo 5.102
Time: 10 June, 2022, 14:00