The long-term goal of the project is to develop and analyse methods for the recognition of specific nano-objects by analysing data-intensive, noisy, and artefact afflicted image sequences from sensor systems, which are subject to several aggravating influences. A challenge is that the processing of the image sequences should be done in (soft) real-time while minimising resource consumption, e.g., of energy and memory. Therefore, multi-objective optimisation is an important topic of our research. Amongst other objectives, we optimise hardware efficiency, time efficiency, and detection quality regarding varying demands. At the centre of attention are the detection and quantification of biological nanoparticles with the plasmon assisted microscopy of nano-sized objects (PAMONO) sensor. Topics of consideration include aspects of technological development and biophysical methods for nano-object detection in vital, real-life scenarios.
Based on the experience from the project, we aim to develop methods and technical concepts with respect to robustness and applicability to identify the most feasible methods for fast, user-friendly sensor software adaptation in the field of quality control of medicinal products. This should be achieved in collaboration with the application partners ARTES Biotechnology GmbH (ARTES) and Paul-Ehrlich-Institut (PEI). They are involved in the methodological development and especially responsible for the subsequent commercial aspects of the PAMONO sensor in fields of quality control in the production of vaccines (ARTES) and quality control of blood donations and blood products (PEI). A challenge is to adapt to altering environmental conditions and thus to increasingly diverse characteristics of images. For this purpose, we want to examine methods that increase adaptivity of deep feature learning approaches and develop highly specialised, efficient architectures for DNNs (differentiable programming). At the technical level, we will focus on the development of novel approaches for PAMONO sensor surface functionalisation and of an innovative, adaptive biosensor/actuator unit based on the PAMONO sensor. Therefore, algorithmic solutions for automatic adjustment of the involved actuators and automatic monitoring of the PAMONO unit sensor behaviour are needed. As a result of the project, we want to achieve a methodical and technical solution that allows for using the PAMONO technology for medicinal product quality control.
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