Topic Description:
Camera traps are widely used in wildlife monitoring, but automated species recognition remains challenging due to low image quality, occlusions, and morphological similarities between species. Most existing approaches rely on single-frame classification, disregarding valuable t...
Video-based animal re-identification has the potential to outperform image-based approaches by leveraging not only spatial but also temporal features. However, progress in this field is severely hindered by the lack of publicly available datasets. To address this, our group has developed one of the ...
Depression is one of the most common mental health disorders, significantly reducing an individual’s quality of life. Psychologists use various methods to detect and assess depression, such as analysing facial expressions, speech patterns, and head movements. In this research, our goal is to detect ...
Background
Current our project relies only on raw time-series IMU data for word/sentence-based online handwriting recognition. However, handwriting motion contains patterns that may be more distinguishable in the frequency domain. By converting IMU signals into spectrograms, we capture both tempora...
Project / Research Internship
Background
Are you interested in clinical research, data analysis, and exploring the real-world challenges of digital health technologies? Join our research team to analyze data from a clinical trial investigating the effects of physiotherapy and home-based training i...
Bachelor's / Master's Thesis / Research Internship / Project
Fear avoidance (FA) beliefs (i.e. movements may lead to pain/injury) motivate patients with chronic primary low back pain (CPLBP) to avoid physical activity and may thereby contribute to the maintenance of pain and disability. Patients’ c...
This project aims to develop an open-source online platform in the domain of gaze and eye-tracking research. The platform will be hosted on GitBook/GitHub, enabling robust version control and collaboration. A key focus will be establishing interoperability standards. Additionally, the project will i...
Description:
This project focuses on developing a deep learning model that accurately segments tissues in a wound by incorporate prior knowledge about the wound structure using spatial priors. This targeted solution aims to streamline the tissue segmentation process, ultimately contributing to the...
Description:
This project focuses on developing a deep learning model that accurately segments tissues in a wound using super pixel based image segmentation algorithms. This targeted solution aims to streamline the tissue segmentation process, ultimately contributing to the SWODDYS project's large...
Bachelor's / Master's Thesis / Research Internship / Project
Earliest project/thesis start in May 2025!
The real-time control and analysis of human poses and movements has long been a complex problem in fields like computer vision and machine learning. Physics-informed neural networks (PINNs) have...
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