| iCCC2024 - iCampµs Cottbus Conference |
7.4 - Polycrystalline Nb2O5 Compared on Constant-Capacitance Structures and on Ion-Sensitive Field-Effect Transistors for pH-Sensing |
C. Beale, M. Wambold, P. Bott, L. Kühne, F. Al-Falahi, E. Kurth, O. Hild - Fraunhofer IPMS, Dresden |
| iCCC2024 - iCampµs Cottbus Conference |
I11 - Sensoren für Grand Challenges |
U. Panne - Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin |
| iCCC2024 - iCampµs Cottbus Conference |
8.2 - KUNSTBLUT - Artificial Blood for Experimental Flow Visualization in Intracranial Aneurysms |
C. Winkler, G. Hentschel, M. Müller, B. Glasmacher - Leibniz Universität Hannover, Garbsen , P. Berg - Otto-von-Guericke-Universität Magdeburg, Magdeburg, K. Zähringer - Otto-von-Guericke-Universität Magdeburg, Magdeburg, F. Rummel - NETZSCH-Gerätebau GmbH, Selb |
| iCCC2024 - iCampµs Cottbus Conference |
8.3 - Optofluidic biosensors with Si-based photonic integrated circuit technology |
P. Steglich, M. Paul, G. Lecci, C. Schumann - HyPhoX, Wildau, A. Mai - Technische Hochschule Wildau, Wildau |
| iCCC2024 - iCampµs Cottbus Conference |
8.4 - Si-kompatible Schottky SWIR-Detektortechnologie für Anwendungen in der Gassensorik |
L. Augel, H. Wen, J. Knobbe - Fraunhofer IPMS, Dresden |
| iCCC2024 - iCampµs Cottbus Conference |
P1 - Prototype of an energy harvesting sensor with wireless data transmission |
A. Bürger, S. Simon, S. Hernschier - Brandenburgische Technische Universität Cottbus-Senftenberg, Cottbus |
| iCCC2024 - iCampµs Cottbus Conference |
P2 - VibroMote: Energy efficient Vibration Monitoring for Railway tracks and Bridges |
N. Chatharajupalli, R. Rotta, J. Nolte - Brandenburgische Technische Universität Cottbus-Senftenberg, Cottbus |
| iCCC2024 - iCampµs Cottbus Conference |
P3 - Anomaly Detection of Rotating and Oscillating Bearings using Autoencoder |
J. Diez, L. Mattenklodt, A. Dittmer, J. Windelberg - German Aerospace Center - Institut FT, Brunswick |
| iCCC2024 - iCampµs Cottbus Conference |
P4 - Redundancy-orchestrated Information Fusion Exploiting Sensor Redundancy for Improved Model Robustness |
C. Holst - inIT – Institut für industrielle Informationstechnik, Technische Hochschule Ostwestfalen-Lippe, Lemgo |
| iCCC2024 - iCampµs Cottbus Conference |
P5 - Explanatory predictive inference for the maintenance process using a deep learning approach |
D. Szarek, A. Wylomanska - Wroclaw University of Technology,Wroclaw (Poland), I. Jablonski - Brandenburgische Technische Universität Cottbus-Senftenberg, Cottbus |
