Funding period: 01/2023 – 06/2026 Many industries are transitioning to Industry 4.0 production models by adopting robots in their processes. In parallel, Extended Reality (XR) technologies have reached sufficient maturity to enter the industrial applications domain, with early success cases often related to training workers, remote assistance, access to contextual Read more…
We present an interactive image captioning pipeline. Image captioning models take an image as input, for which they generate one or more captions, or descriptions in natural language. State-of-the-art image captioning systems are trained in an offline mode, namely with a big amount of data at once. With our approach, Read more…
Contract cheating, an academic dishonesty when students ask another person to take an exam or to do an assignment instead of them, turns out to be a significant and growing problem, receiving a large amount of media coverage. It becomes a mature industry with a lot of specialized websites full Read more…
Medical image analysis encompasses two crucial research areas: disease grading and fine-grained lesion segmentation. Although disease grading often relies on fine-grained lesion segmentation, they are usually studied separately. Disease severity grading can be approached as a classification problem, utilizing image-level annotations to determine the severity of a medical condition. On Read more…
Figure 1: The interface guides annotators in human evaluation. Snippet A displays the original oncology report with highlighted sentences extracted automatically. Snippet C lets annotators choose the model for generation, showing its architecture. The middle section (B) presents the chosen model’s generation results, with green words denoting the most learned Read more…
Funding period 03/2021 – 03/2024 Ophthalmo-AI focuses on the two most common causes of blindness in people aged 50 and older: Age-related macula degeneration (AMD) and diabetic retinopathy (DR). An intelligent assistance system is under development to support ophthalmologists using image data and clinical data to reach a correct medical Read more…
Funding Period: 10/2020 – 9/2023 To broaden the use of AI methods in medicine, networked, digital patient data is required, for example for use in disease diagnosis, personalized treatment, and faster drug discovery. Our project pAItient (AI innovation center with integrated, rights-protected environment for the development, testing, and clinical assessment Read more…