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…