Machine Learning is currently world-wide a very active research area. In particular, deep learning methods have become very popular in the last decade, which use very large and carefully constructed artificial neural networks (ANN) for storing knowledge models. In our research group we focus on innovative applications for machine learning technology. Depending on the particular application we use technologies like unsupervised and supervised learning and reinforcement learning.
If ML models are used in an application, the information from the readily trained ANN is recalled. This process is known as ML-inference. ML-inferece can be done on specially designed embedded processors. These may be called TPUs (tensor processing unit), VPU (visual processing unit) and others. Often applications require small sized networked and embedded computers. The research area around ML-inference on embedded devices is called Embedded Machine Learning.
Here you will find a selection student papers (thesis, homework assignments, summaries etc) around applications in machine learning.