Das Projekt „DeepSpoMed – Neuartige Auswertung von Thermografiekameradaten mittels neuronaler Netze“ ist Teil des Kooperationsprojektes „Innovative sportmedizinische Leistungsdiagnostik, basierend auf einer neuartigen Auswertung von Thermografiekameradaten mittels neuronaler Netze – InnoSpoMed“.
Das Projekt ist eine Zusammenarbeit von
Das Projekt wird durch das Bundesministerium für Wirtschaft und Energie (BMWi) im Rahmen des Förderprogramms „Zentrale Innovation Mittelstand“ (ZIM) gefördert.
2023
Hillen, B., Zentgraf, S., Weber, V., et al. (2023, Juli 7). Poster | Deep neural network-driven time series analysis of posterior legs surface radiation during cardiopulmonary exercise testing and associations with core temperature and internal load. 28th Annual Congress of the European College of Sport Science (ECSS), Paris.
Hillen, B., Andrés López, D., Marzano Felisatti, J. M., et al. (2023, Juni 27). Poster | Skin thermal radiation variation during a pyramidal load cycling protocol and the association with individual load and thermoregulation. Sports, Medicine and Health Summit, CCH Hamburg.
Andrés López, D., Hillen, B., Simon, P., Schömer, E. (2023). Presentation | Improved deep neural network-driven automatic segmentation of skin’s thermal radiation in moving posterior legs during cardiopulmonary exercise testing for time series data analysis (A. Kiadó, Hrsg.).
Hillen, B., Lopez, D. A., Marzano-Felisatti, J. M., et al. (2023). Acute physiological responses to a pyramidal exercise protocol and the associations with skin temperature variation in different body areas. JOURNAL OF THERMAL BIOLOGY, 115. DOI Author/Publisher URL
Hillen, B., Lopez, D. A., Pfirrmann, D., et al. (2023). An exploratory, intra- and interindividual comparison of the deep neural network automatically measured calf surface radiation temperature during cardiopulmonary running and cycling exercise testing: A preliminary study. JOURNAL OF THERMAL BIOLOGY, 113. DOI Author/Publisher URL
2022
Hillen, B., Lopez, D. A., Schömer, E., et al. (2022). Towards Exercise Radiomics: Deep Neural Network-Based Automatic Analysis of Thermal Images Captured During Exercise. IEEE Journal of Biomedical and Health Informatics, 1-11. DOI
2020
Andrés López, D., Hillen, B., Simon, P., und Schömer, E. (2020). Presentation | Deep learning based segmentation of uncovered body parts in thermal images during dynamic exercise. Book of Abstracts, 24-25. Author/Publisher URL
Andrés López, D., Hillen, B., Simon, P., und Schömer, E. (2020). Presentation | Thermonet: Automatic Segmentation of Blood Vessel Patterns detected by Infrared Thermography during dynamic Exercise (F. Dela, E. Müller, und E. Tsolakidis, Hrsg.; Nummer Book of Abstracts, S. 127-127). Author/Publisher URL
