Zobrazeno 1 - 10
of 19 677
pro vyhledávání: '"Verhoef BE"'
Autor:
Spaanderman, Douwe J., Marzetti, Matthew, Wan, Xinyi, Scarsbrook, Andrew F., Robinson, Philip, Oei, Edwin H. G., Visser, Jacob J., Hemke, Robert, van Langevelde, Kirsten, Hanff, David F., van Leenders, Geert J. L. H., Verhoef, Cornelis, Gruühagen, Dirk J., Niessen, Wiro J., Klein, Stefan, Starmans, Martijn P. A.
Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with variable clinical behaviours and treatment approaches. This systematic review provides an overview of Artificial Intelligence (AI) methods using radiological imagin
Externí odkaz:
http://arxiv.org/abs/2408.12491
Humans have clear cross-modal preferences when matching certain novel words to visual shapes. Evidence suggests that these preferences play a prominent role in our linguistic processing, language learning, and the origins of signal-meaning mappings.
Externí odkaz:
http://arxiv.org/abs/2407.17974
Natural language has the universal properties of being compositional and grounded in reality. The emergence of linguistic properties is often investigated through simulations of emergent communication in referential games. However, these experiments
Externí odkaz:
http://arxiv.org/abs/2407.17960
Recent advances in computational linguistics include simulating the emergence of human-like languages with interacting neural network agents, starting from sets of random symbols. The recently introduced NeLLCom framework (Lian et al., 2023) allows a
Externí odkaz:
http://arxiv.org/abs/2407.13999
Autor:
Raaijmakers, Stephan, Bakker, Roos, Cremers, Anita, de Kleijn, Roy, Kouwenhoven, Tom, Verhoef, Tessa
Conversational AI systems that rely on Large Language Models, like Transformers, have difficulty interweaving external data (like facts) with the language they generate. Vanilla Transformer architectures are not designed for answering factual questio
Externí odkaz:
http://arxiv.org/abs/2402.19218
Autor:
Spaanderman, Douwe J., Starmans, Martijn P. A., van Erp, Gonnie C. M., Hanff, David F., Sluijter, Judith H., Schut, Anne-Rose W., van Leenders, Geert J. L. H., Verhoef, Cornelis, Grunhagen, Dirk J., Niessen, Wiro J., Visser, Jacob J., Klein, Stefan
Segmentations are crucial in medical imaging to obtain morphological, volumetric, and radiomics biomarkers. Manual segmentation is accurate but not feasible in the radiologist's clinical workflow, while automatic segmentation generally obtains sub-pa
Externí odkaz:
http://arxiv.org/abs/2402.07746
Autor:
Verhoef, Bart J., Lu, Xixi
Previous studies have used prescriptive process monitoring to find actionable policies in business processes and conducted case studies in similar domains, such as the loan application process and the traffic fine process. However, care processes ten
Externí odkaz:
http://arxiv.org/abs/2310.00981
Missing diversity, equity, and inclusion elements in affective computing datasets directly affect the accuracy and fairness of emotion recognition algorithms across different groups. A literature review reveals how affective computing systems may wor
Externí odkaz:
http://arxiv.org/abs/2309.10780
Autor:
Li, Yunqiang, van Gemert, Jan C., Hoefler, Torsten, Moons, Bert, Eleftheriou, Evangelos, Verhoef, Bram-Ernst
Deep learning algorithms are increasingly employed at the edge. However, edge devices are resource constrained and thus require efficient deployment of deep neural networks. Pruning methods are a key tool for edge deployment as they can improve stora
Externí odkaz:
http://arxiv.org/abs/2307.08483
Publikováno v:
Journal of Patient-Reported Outcomes, Vol 8, Iss 1, Pp 1-13 (2024)
Abstract Background The Otology Questionnaire Amsterdam (OQUA) is developed to evaluate multiple ear complaints and their impact on patients’ daily lives. The current clinical use of this questionnaire is below the potential utilization. Aim To ide
Externí odkaz:
https://doaj.org/article/dfdd532e70ce40d1b363de7aa222f457
