TY - JOUR A1 - Augustine, Nitin A1 - Schwab, Maximilian A1 - Klarmann, Steffen A1 - Pfefferer, Christian A1 - Schiendorfer, Alexander T1 - Impact of Blemish Artefacts on Object Detection Models in Autonomous Driving: A Study on Camera Module Manufacturing Defects JF - Procedia Computer Science N2 - With the rise of autonomous driving technology, concerns over the safety of AI-based systems have increased, particularly regarding their effect on human life and infrastructure. The complexity and unpredictable nature of AI-enabled software functions have disrupted traditional safety evaluation methods. In such a scenario, the quality control methods used at the manufacturing environments of sensors used for deploying AI-based perception functions need to be coupled with the downstream functions. This study focuses on investigating the impact of a specific production-related defect called blemish, which is caused by debris on image sensors of camera modules. The research aims to answer two fundamental questions: 1) How can blemish artifacts be mathematically modeled, and what is the process for developing a suitable dataset that incorporates this defect? 2) How can the influence of blemish artifacts on performance of object detection models be traced back to define quality requirements of the camera modules? This work takes a novel perspective by shifting the focus from improving model resilience to improving hardware quality camera modules by studying the effects of manufacturing defects on downstream functions. This research seeks to establish a framework to derive quality targets for front camera module manufacturing which can be extended to other sensors for similar applications. UR - https://doi.org/10.1016/j.procs.2024.01.061 Y1 - 2024 UR - https://doi.org/10.1016/j.procs.2024.01.061 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-46388 SN - 1877-0509 VL - 2024 IS - 232 SP - 616 EP - 625 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Schiendorfer, Alexander A1 - Steghöfer, Jan-Philipp A1 - Reif, Wolfgang T1 - Synthesis and Abstraction of Constraint Models for Hierarchical Resource Allocation Problems T2 - Proceedings of the 6th International Conference on Agents and Artificial Intelligence: Volume 2: ICAART N2 - Many resource allocation problems are hard to solve even with state-of-the-art constraint optimisation software upon reaching a certain scale. Our approach to deal with this increasing complexity is to employ a hierarchical “regio-central” mechanism. It requires two techniques: (1) the synthesis of several models of agents providing a certain resource into a centrally and efficiently solvable optimisation problem and (2) the creation of an abstracted version of this centralised model that reduces its complexity when passing it on to higher layers. We present algorithms to create such synthesised and abstracted models in a fully automated way and demonstrate empirically that the obtained solutions are comparable to central solutions but scale better in an example taken from energy management. UR - https://doi.org/10.5220/0004757700150027 Y1 - 2014 UR - https://doi.org/10.5220/0004757700150027 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-42364 SN - 978-989-758-016-1 SP - 15 EP - 27 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Schiendorfer, Alexander A1 - Lassner, Christoph A1 - Anders, Gerrit A1 - Reif, Wolfgang A1 - Lienhart, Rainer T1 - Active Learning for Efficient Sampling of Control Models of Collectives T2 - Proceedings: 2015 IEEE 9th International Conference on Self-Adaptive and Self-Organizing Systems: SASO 2015 UR - https://doi.org/10.1109/SASO.2015.13 Y1 - 2015 UR - https://doi.org/10.1109/SASO.2015.13 SP - 51 EP - 60 PB - IEEE CY - Los Alamitos ER - TY - CHAP A1 - Anders, Gerrit A1 - Siefert, Florian A1 - Schiendorfer, Alexander A1 - Seebach, Hella A1 - Steghöfer, Jan-Philipp A1 - Eberhardinger, Benedikt A1 - Kosak, Oliver A1 - Reif, Wolfgang ED - Reif, Wolfgang ED - Anders, Gerrit ED - Seebach, Hella ED - Steghöfer, Jan-Philipp ED - André, Elisabeth ED - Hähner, Jörg ED - Müller-Schloer, Christian ED - Ungerer, Theo T1 - Specification and Design of Trust-Based Open Self-Organising Systems T2 - Trustworthy Open Self-Organising Systems UR - https://doi.org/10.1007/978-3-319-29201-4_2 Y1 - 2016 UR - https://doi.org/10.1007/978-3-319-29201-4_2 SN - 978-3-319-29201-4 SP - 17 EP - 54 PB - Birkhäuser CY - Cham ER - TY - JOUR A1 - Anders, Gerrit A1 - Schiendorfer, Alexander A1 - Siefert, Florian A1 - Steghöfer, Jan-Philipp A1 - Reif, Wolfgang T1 - Cooperative Resource Allocation in Open Systems of Systems JF - ACM Transactions on Autonomous and Adaptive Systems UR - https://dl.acm.org/doi/10.1145/2700323 Y1 - 2015 UR - https://dl.acm.org/doi/10.1145/2700323 SN - 1556-4665 SN - 1556-4703 VL - 10 IS - 2 PB - ACM CY - New York ER - TY - CHAP A1 - Schiendorfer, Alexander A1 - Anders, Gerrit A1 - Steghöfer, Jan-Philipp A1 - Reif, Wolfgang ED - Nguyen, Ngoc Thanh ED - Kowalczyk, Ryszard ED - Duval, Béatrice ED - van den Herik, Jaap ED - Loiseau, Stephane ED - Filipe, Joaquim T1 - Abstraction of Heterogeneous Supplier Models in Hierarchical Resource Allocation T2 - Transactions on Computational Collective Intelligence XX UR - https://doi.org/10.1007/978-3-319-27543-7_2 Y1 - 2016 UR - https://doi.org/10.1007/978-3-319-27543-7_2 SN - 978-3-319-27543-7 SP - 23 EP - 53 PB - Springer CY - Cham ER - TY - CHAP A1 - Kosak, Oliver A1 - Wanninger, Constantin A1 - Angerer, Andreas A1 - Hoffmann, Alwin A1 - Schiendorfer, Alexander A1 - Seebach, Hella ED - Elnikety, Sameh ED - Lewis, Peter R. ED - Müller-Schloer, Christian T1 - Towards Self-organizing Swarms of Reconfigurable Self-aware Robots T2 - Proceedings: IEEE 1st International Workshops on Foundations and Applications of Self-* Systems (FAS-W 2016) UR - https://doi.org/10.1109/FAS-W.2016.52 Y1 - 2016 UR - https://doi.org/10.1109/FAS-W.2016.52 SN - 978-1-5090-3651-6 SP - 204 EP - 209 PB - IEEE CY - Los Alamitos ER - TY - CHAP A1 - Schiendorfer, Alexander A1 - Wautelet, Yves A1 - Reif, Wolfgang ED - Loiseau, Stephane ED - Filipe, Joaquim ED - Duval, Béatrice ED - van den Herik, Jaap T1 - Modeling Hierarchical Resources Within a Unified Ontology BT - A Position Paper T2 - Proceedings of the International Conference on Agents and Artificial Intelligence N2 - Resource-Intensive Software Ecosystems (RISE) can mainly be found in production management but also in virtually any socio-technical environment. RISE appear prominently in the form of smart grids or cloud environments where optimizing resource utilization and allocation becomes the most important aspect for competitive service provision. In such a context, the need for unified ontologies supported by adaptive software (i.e., software able to learn from and act on its environment) is highly attractive. Indeed, resources are mostly not monolithic entities but active and collaborative agents often organized in a hierarchical manner. A hierarchy implies multiple levels of abstraction leading to resource allocation on different levels of organization -- with abstractions being relevant for both inter- and intra-organization resource management. Once adequately defined, the use of constraint-based optimization algorithms on those multiple levels can provide efficient resource allocation. We apply, in this paper, ontological elements to model resources in a unified manner on multiple levels onto an example taken from distributed energy management. Then we present algorithmic ideas to organize the hierarchy of these resources. UR - https://doi.org/10.5220/0005289006140619 Y1 - 2015 UR - https://doi.org/10.5220/0005289006140619 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-42448 SN - 978-989-758-074-1 SP - 614 EP - 619 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Stieber, Simon A1 - Schröter, Niklas A1 - Fauster, Ewald A1 - Schiendorfer, Alexander A1 - Reif, Wolfgang ED - Wani, M. Arif ED - Sethi, Ishwar ED - Shi, Weisong ED - Qu, Guangzhi ED - Raicu, Daniela Stan ED - Jin, Ruoming T1 - PermeabilityNets: Comparing Neural Network Architectures on a Sequence-to-Instance Task in CFRP Manufacturing T2 - Proceedings: 20th IEEE International Conference on Machine Learning and Applications (ICMLA 2021) UR - https://doi.org/10.1109/ICMLA52953.2021.00116 KW - Sequence-to-Instance Learning KW - Architecture comparison KW - CFRP KW - LCM KW - Industry 4.0 KW - Digital Twin Y1 - 2021 UR - https://doi.org/10.1109/ICMLA52953.2021.00116 SN - 978-1-6654-4337-1 SP - 694 EP - 697 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Stieber, Simon A1 - Schröter, Niklas A1 - Schiendorfer, Alexander A1 - Hoffmann, Alwin A1 - Reif, Wolfgang ED - Dong, Yuxiao ED - Mladenić, Dunja ED - Saunders, Craig T1 - FlowFrontNet: Improving Carbon Composite Manufacturing with CNNs T2 - Machine Learning and Knowledge Discovery in Databases, Applied Data Science Track, Proceedings, Part IV UR - https://doi.org/10.1007/978-3-030-67667-4_25 KW - process monitoring KW - convolutional neural networks KW - digital twin KW - manufacturing KW - industrial automation KW - resin transfer molding KW - carbon composites Y1 - 2021 UR - https://doi.org/10.1007/978-3-030-67667-4_25 SN - 978-3-030-67667-4 SN - 978-3-030-67666-7 N1 - Access to this content is enabled by Nationallizenz Ebooks Medicine SP - 411 EP - 426 PB - Springer CY - Cham ER -