Auflistung nach Autor:in "Sonntag, Daniel"
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- ZeitschriftenartikelA Paradigm Shift in Healthcare Provision(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Sonntag, Daniel; Gelissen, Jean
- JournalAI in Germany: Well-Prepared and Eager to Do Something(KI - Künstliche Intelligenz: Vol. 32, No. 2-3, 2018) Sonntag, Daniel
- ZeitschriftenartikelAI in Medicine, Covid-19 and Springer Nature's Open Access Agreement(KI - Künstliche Intelligenz: Vol. 34, No. 2, 2020) Sonntag, Daniel
- KonferenzbeitragAssessing the quality of natural language text data(Informatik 2004 – Informatik verbindet – Band 1, Beiträge der 34. Jahrestagung der Gesellschaft für Informatik e.V. (GI), 2004) Sonntag, DanielWe follow an empirical approach from data quality toward text quality, where the expectations of the consumer, human or machine, take the centre stage. We try to obtain numerical text quality statements which must be interpreted for the expectations of the user and suitability for automatic natural language processing (NLP) separately. We state that apart from text accessibility today only representational text quality metrics can be derived and computed automatically. Interestingly, text quality for NLP traces back to questions of text representation.
- ZeitschriftenartikelAvoid Predatory Journals(KI - Künstliche Intelligenz: Vol. 37, No. 1, 2023) Sonntag, Daniel
- ZeitschriftenartikelAvoid Predatory Journals(KI - Künstliche Intelligenz: Vol. 37, No. 1, 2023) Sonntag, Daniel
- ZeitschriftenartikelCollaborative Multimodality(KI - Künstliche Intelligenz: Vol. 26, No. 2, 2012) Sonntag, DanielThis essay is a personal reflection from an Artificial Intelligence (AI) perspective on the term HCI. Especially for the transfer of AI-based HCI into industrial environments, we survey existing approaches and examine how AI helps to solve fundamental problems of HCI technology. The user and the system must have a collaborative goal. The concept of collaborative multimodality could serve as the missing link between traditional HCI and intuitive human-centred designs in the form of, e.g., natural language interfaces or intelligent environments. Examples are provided in the medical imaging domain.
- ZeitschriftenartikelPartial Image Active Annotation (PIAA): An Efficient Active Learning Technique Using Edge Information in Limited Data Scenarios(KI - Künstliche Intelligenz: Vol. 38, No. 3, 2024) Kadir, Md Abdul; Alam, Hasan Md Tusfiqur; Srivastav, Devansh; Profitlich, Hans-Jürgen; Sonntag, DanielActive learning (AL) algorithms are increasingly being used to train models with limited data for annotation tasks. However, the selection of data for AL is a complex issue due to the restricted information on unseen data. To tackle this problem, a technique we refer to as Partial Image Active Annotation (PIAA) employs the edge information of unseen images as prior knowledge to gauge uncertainty. This uncertainty is determined by examining the divergence and entropy in model predictions across edges. The resulting measure is then applied to choose superpixels from input images for active annotation. We demonstrate the effectiveness of PIAA in multi-class Optical Coherence Tomography (OCT) segmentation tasks, attaining a Dice score comparable to state-of-the-art OCT segmentation algorithms trained with extensive annotated data. Concurrently, we successfully reduce annotation label costs to 12%, 2.3%, and 3%, respectively, across three publicly accessible datasets (Duke, AROI, and UMN).
- ZeitschriftenartikelSpace Robotics Means Business(KI - Künstliche Intelligenz: Vol. 28, No. 2, 2014) Sonntag, Daniel
- ZeitschriftenartikelSpecial Issue on Health and Wellbeing(KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Gelissen, Jean; Sonntag, DanielThis special issue of KI Journal on health and wellbeing brings together a collection of articles on self-monitoring (quantified-self) related to health and habits (these solutions should reduce the costly demand for secondary prevention) and big health data analysis towards clinical data intelligence for individualized patient treatment. Others include invited contributions on intelligent user interfaces for health and wellbeing. The articles in this collection address diverse aspects of AI methods in the patient/user centric view, the doctor/clinical view, or the combination of these two views.