Clausing, L. (2021). ReconO: High-Performance Embedded Computing for Industrial Analytics on a Reconfigurable System-on-Chip. Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies.https://doi.org/10.1145/3468044.3468056 
LibreCat: /record/30909
DOI: 10.1145/3468044.3468056

Ghasemzadeh Mohammadi, H., Jentzsch, F., Kuschel, M., Arshad, R., Rautmare, S., Manjunatha, S., Platzner, M., Boschmann, A., &; Schollbach, D. (2021). FLight: FPGA Acceleration of Lightweight DNN Model Inference in Industrial Analytics. https://doi.org/10.1007/978-3-030-93736-2_27__Machine Learning and Principles and Practice of Knowledge Discovery in Databases.https://doi.org/10.1007/978-3-030-93736-2_27 
LibreCat: /record/30908
DOI: https://doi.org/10.1007/978-3-030-93736-2_27

Guetttatfi, Z., Kaufmann, P., &; Platzner, M. (2020). Optimal and Greedy Heuristic Approaches for Scheduling and Mapping of Hardware Tasks to Reconfigurable Computing Devices. In Proceedings of the International Workshop on Applied Reconfigurable Computing (ARC).
LibreCat: /record/3583

Chandrakar, K. (2020). Comparison of Feature Selection Techniques to Improve Approximate Circuit Synthesis.
LibreCat: /record/21324

Henke, L.-S. (2020). Evaluation of a ReconOS-ROS Combination based on a Video Processing Application.
LibreCat: /record/21432

Gatica, C. P., &; Platzner, M. (2020). Adaptable Realization of Industrial Analytics Functions on Edge-Devices using Reconfigurable Architectures. In Machine Learning for Cyber Physical Systems (ML4CPS 2017). Berlin, Heidelberg.https://doi.org/10.1007/978-3-662-59084-3_9 
LibreCat: /record/21584
DOI: 10.1007/978-3-662-59084-3_9

Witschen, L. M., Wiersema, T., &; Platzner, M. (2020). Proof-carrying Approximate Circuits. IEEE Transactions On Very Large Scale Integration Systems, 28(9), 2084–2088.https://doi.org/10.1109/TVLSI.2020.3008061 
LibreCat: /record/17358
DOI: 10.1109/TVLSI.2020.3008061

Ho, N., Kaufmann, P., &; Platzner, M. (2020). Evolution of Application-Specific Cache Mappings. International Journal of Hybrid Intelligent Systems.
LibreCat: /record/17369

Witschen, L. M., Wiersema, T., &; Platzner, M. (n.d.). Search Space Characterization for AxC Synthesis. Fifth Workshop on Approximate Computing (AxC 2020).
LibreCat: /record/20748

Lienen, C., Platzner, M., &; Rinner, B. (2020). ReconROS: Flexible Hardware Acceleration for RO Applications. In Proceedings of the 2020 International Conference on Field-Programmable Technology (FPT).
LibreCat: /record/20750

Thiele, S. (2020). Implementing Machine Learning Functions as PYNQ FPGA Overlays.
LibreCat: /record/20820

Jaganath, V. (2020). Extension and Evaluation of Python-based High-Level Synthesis Tool Flows.
LibreCat: /record/20821

Hansmeier, T., Kaufmann, P., &; Platzner, M. (2020). An Adaption Mechanism for the Error Threshold of XCSF. GECCO ’20: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1756–1764.https://doi.org/10.1145/3377929.3398106 
LibreCat: /record/17063
DOI: 10.1145/3377929.3398106

Anwer, J., Meisner, S., &; Platzner, M. (2020). Dynamic Reliability Management for FPGA-Based Systems. International Journal of Reconfigurable Computing, 1–19.https://doi.org/10.1155/2020/2808710 
LibreCat: /record/17092
DOI: 10.1155/2020/2808710

Bellman, K., Dutt, N., Esterle, L., Herkersdorf, A., Jantsch, A., Landauer, C.,  Tammemäe, K. (2020). Self-aware Cyber-Physical Systems. ACM Transactions on Cyber-Physical Systems, Accepted for Publication, 1–24.
LibreCat: /record/15836

Awais, M., Ghasemzadeh Mohammadi, H., &; Platzner, M. (2020). A Hybrid Synthesis Methodology for Approximate Circuits. In Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020 (pp. 421–426). Beijing, China: ACM.https://doi.org/10.1145/3386263.3406952 
LibreCat: /record/16213
DOI: 10.1145/3386263.3406952

Hansmeier, T., Kaufmann, P., &; Platzner, M. (2020). Enabling XCSF to Cope with Dynamic Environments via an Adaptive Error Threshold. In GECCO ’20: Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 125–126). New York, NY, United States: Association for Computing Machinery (ACM).https://doi.org/10.1145/3377929.3389968 
LibreCat: /record/16363
DOI: 10.1145/3377929.3389968

Lösch, A., &; Platzner, M. (2020). MigHEFT: DAG-based Scheduling of Migratable Tasks on Heterogeneous Compute Nodes. 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).https://doi.org/10.1109/ipdpsw50202.2020.00012 
LibreCat: /record/20838
DOI: 10.1109/ipdpsw50202.2020.00012

Jentzsch, F. P. (2020). Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture.
LibreCat: /record/21433

Lösch, A., &; Platzner, M. (2020). MigHEFT: DAG-based Scheduling of Migratable Tasks on Heterogeneous Compute Nodes. 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 6–16.https://doi.org/10.1109/IPDPSW50202.2020.00012 
LibreCat: /record/35152
DOI: 10.1109/IPDPSW50202.2020.00012