Projects
Multi-modal signal processing algorithms for extraction of coupled sources in combined audio and EEG recordings. KU Leuven
One in five experiences hearing loss. The World Health Organization estimates that this number will increase to one in four in 2050. Luckily, effective hearing devices such as hearing aids and cochlear implants exist with advanced noise suppression and speaker enhancement algorithms that can significantly improve the quality of life of people suffering from hearing loss. State-of-the-art hearing devices, however, underperform in a so-called ...
Exploiting scene constraints to improve object detection algorithms for industrial applications KU Leuven
State-of-the-art object detection algorithms are designed to be heavily robust against scene and object variations like illumination changes, occlusions, scale changes, orientation differences, background clutter and object intra-class variability. However, in industrial machine vision applications, where objects with variable appearance have to be detected, many of these variations are in fact constant and can be seen as scene specific ...
Digital Signal Processing Algorithms for Noise Reduction, Dynamic Range Compression, and Feedback Cancellation in Hearing Aids KU Leuven
Algorithms to solve 2D and 3D Irregular Cutting and Packing Problems using a Semi-discrete Representation KU Leuven
Cutting and packing problems, whether in 2D or 3D, involve positioning a set of pieces without overlap within one or more containers. These problems occur in a wide range of industrial applications such as sheet metal and textile cutting, logistics, and additive manufacturing. This thesis provides efficient optimization methods for both 2D and 3D irregular cutting and packing problems using a semi-discrete representation of both the pieces ...
How algorithms are augmenting the journalistic institution: In search of evidence from newsrooms and its innovation labs KU Leuven
How algorithms are augmenting the journalistic institution: In search of evidence from newsroom innovation labs
Digitalization has dramatically changed newsrooms in recent years; for example, journalists increasingly use tools to gather, write, verify, and disseminate news. These tools, in the form of algorithms, are latent in the news ecosystem and take the form of recommender systems (labeling what is newsworthy), speech-to-text ...
Designing Anomaly Detection Algorithms that Exploit Flexible Supervision KU Leuven
Anomaly detection is the task of identifying observations in a dataset that do not conform the expected behavior. It is a crucial data mining task as in the real world, anomalous observations often correspond to real costs. For example, a machine that breaks, a fraudulent credit card transaction, or a patient experiencing irregular heart rhythms. With the advent of big data, manually sifting through millions of observations to detect the ...
Decomposition-based algorithms for optimization problems KU Leuven
Despite the recent very significant progress concerning algorithms for combinatorial optimization problems, most large instances of NP-Hard problems remain intractable by general solvers, motivating the development of problem-specific (meta)heuristic algorithms. While often resulting in acceptable results, the development of problem-specific algorithms is time-consuming and traditionally very expensive. In response to these shortcomings, this ...
DSP Algorithms for Ad-Hoc Wireless Transducer Array Networks KU Leuven
The quality of a speech signal recorded through multiple microphones can be compromised by various undesired signals, including noise and reverberation, leading to diminished intelligibility. Some of these undesired signals may be generated by loudspeakers within the same acoustic environment, potentially generating acoustic echoes and/or feedback. Multi-microphone speech enhancement systems aim at suppressing or canceling these interference ...