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Joakim Haurum conducts applied fundamental research in Computer Vision and Machine Learning, focusing on analyzing novel problems grounded in real-world applications. He is particularly interested in fine-grained image analysis and expert tasks in biodiversity monitoring and open-world recognition. Joakim holds a PhD in Computer Vision, where he specialized in Deep Dive Computer Vision Aided Sewer Inspections. His interdisciplinary approach combines insights from various domains to advance automated systems for analyzing visual data. He has contributed numerous publications and has been involved in multiple research projects, including the development of datasets aimed at improving biodiversity monitoring.
Aalborg University • Aalborg, Denmark
Conducted research on deep learning techniques for sewer inspections.
Requirements apply generally to Master's programs across departments including Sociology, Business, and Engineering at Aalborg University.