Federated Learning with Rebalanced Dataset

With the widespread application of artificial intelligence, centralized machine learning approaches, which require access to users' local data, have raised concerns about data privacy. In response, federated learning, an architecture that aggregates models trained locally with local data, has been proposed. This approach addresses the data...

Positive Eating: Fostering Wellbeing in Healthy Eating Experiences Supported by AI-Driven Systems

Is healthy eating simply the intake of correct quantities of certain nutrients, regardless of how and where? This project addresses improving wellbeing within the broad context of eating. <br/><br/>Eating-related guidance products have a hyper-focus on nutrition and/or weight loss, to the detriment of a wider definition of “health”. Wellbeing is...

Spiking Neural Networks Based Data Driven Control: An Illustration Using Cart-Pole Balancing Example

Machine learning can be effectively applied in control loops to robustly make optimal control decisions. There is increasing interest in using spiking neural networks (SNNs) as the apparatus for machine learning in control engineering, because SNNs can potentially offer high energy efficiency and new SNN-enabling neuromorphic hardwares are being...

Tennis Stroke Recognition: Stroke classification using inertial measuring unit and machine learning algorithm in Tennis

One interesting part of the application of human activity recognition is sports motion recognition and classification. In recent years, many commercial wearable devices have been used for recording and supervising motion data information during sports. However, their claimed high-accuracy results but motion recognition and classification method...