Low-Power Gesture Recognition Using Convolutional Neural Networks and Ambient Lighting

This paper presents a study focused on developing an efficient signal processing pipeline and identifying suitable machine learning models for real-time gesture recognition using a testbed consisting of an Arduino Nano 33 BLE and three OPT101 photodiodes. Our research aims to address the challenges of limited computational power whilst...

Deep Just-in-Time Defect Prediction at Adyen

Finding defects in proposed changes is one of the biggest motivations and expected outcomes of code review, but does not result as often as expected in actually finding defects. Just-in-time (JIT) defect prediction focuses on predicting bug-introducing changes, which can help with efficient allocation of inspection time according to the defect...

Machine learning based time-series postprocessing for the interferometric SAR remote sensing data

A satellite remote sensing technique, Interferometric Synthetic Aperture Radar (InSAR), is able to provide surface displacement information on a millimeter level. In this study, data from the TerraSAR-X satellite collected in the years 2009-2018 over the area of Amsterdam is used. Even though radar data is a subject to multi-step processing,...

Relating groundwater heads to stream discharge by using machine learning techniques: A case study in subcatchment Chaamse Beken

Waterschap Brabantse Delta (WBD) has the intention to implement measures that enhance the baseflow. Baseflow consists of the groundwater flow and a small part of the interflow. During dry periods, streams are dependent on the baseflow. Enhancing the baseflow has a proper effect on the ecologically relevant quality of waters, and is therefore...

ETA prediction for containerships at the Port of Rotterdam using Machine Learning Techniques

The hinterland transportation of incoming containers at container terminals is a complex problem, due to the various actors involved and their often conflicting interests. A promising solution towards the problem for hinterland network operators is that of synchromodality, a concept that refers to on-line network planning for hinterland...

Predicting dairy cow parturition using real-time behavior data from accelerometers: A study in commercial setting

Enhancing Real-Time Twitter Filtering and Classification using a Semi-Automatic Dynamic Machine Learning setup approach

Twitter contains massive amounts of user generated content that also contains a lot of valuable information for various interested parties. Twitcident has been developed to process and filter this information in real-time for interested parties by monitoring a set of predefined topics, exploiting humans as sensors. An analysis of the relevant...

Kernel based LTI and LPV subspace identification: A synergy between machine learning and system identification methods

System identification is the art of constructing mathematical models from observed data. It is a well established field with a history of over 40 years, characterized by a rich theoretical background, while it has proven its worth in many real life applications. On the other hand, Gaussian processes form a specific category of kernel based...

Real-time estimation of surgical procedure duration

Each surgical procedure varies in length. There’s a need for dynamic planning to have an optimal patient flow from their beds to the operating room. This paper proposes an adaptive system that predicts the end of a gallbladder removal surgery 25 minutes in advance with the use of Support Vector Machines based on the activations of the...