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LISA (Laboratory of Image Synthesis and Analysis) brings together expertise in image processing and analysis, pattern recognition, image synthesis and virtual reality. Its LISA-IA unit focuses on the fields of image analysis and pattern recognition and develops new methods for 2D and 3D object segmentation, recognition or tracking, multi-modal image registration, as well as machine and deep learning methods for signal and image processing. In the latter context, research is being carried out on the ability to deal with imperfect (weak or noisy) annotations and on methods of evaluating algorithms in such situations where the ground truth is not available. Developed algorithms are related to biomedical and industrial applications. Following a problem-centered approach, the unit tackles all hardware and software aspects of the chain in multidisciplinary teams (MDs, biologists, engineers, computer scientists, mathematicians, as well as art historians and archaeologists) over multi-institutional collaborations to deliver functional applications. The research is funded both by institutional/public funds and industry collaborations. LISA's achievements include one patent, several highly cited biomedical papers, implementation of acquisition and thermoregulation devices for live cell imaging, multi-media event organization and international cultural heritage projects.
Assessing Intellectual Property Relevant Similarities In Images Through Algorithmic Decision Systems
The project aims at defining whether and how algorithmic technologies could be used to help in assessing, intellectual property (IP) relevant similarities, with a focus on image recognition technologies. Such, algorithmic decision systems (ADS) are currently being developed and used by private companies for, the purposes of IP enforcement (monitoring infringing goods online, filtering out content) and, registration by IP Offices, outside of public scrutiny.