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354 Publications


2017 | Conference Paper | LibreCat-ID: 10780
Guettatfi, Zakarya, et al. “Computational Self-Awareness as Design Approach for Visual Sensor Nodes.” 12th International Symposium on Reconfigurable Communication-Centric Systems-on-Chip (ReCoSoC), 2017, pp. 1–8, doi:10.1109/ReCoSoC.2017.8016147.
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2017 | Conference Paper | LibreCat-ID: 10672
Ho, Nam, et al. “Accurate Private/Shared Classification of Memory Accesses: A Run-Time Analysis System for the LEON3 Multi-Core Processor.” Proc. Design, Automation and Test in Europe Conf. (DATE), 2017, doi:10.23919/DATE.2017.7927096.
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2017 | Conference Paper | LibreCat-ID: 10761
Kaufmann, Paul, et al. “Evaluation Methodology for Complex Non-Deterministic Functions: A Case Study in Metaheuristic Optimization of Caches.” Adaptive Hardware and Systems (AHS), IEEE, 2017, doi:10.1109/AHS.2017.8046380.
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2017 | Book | LibreCat-ID: 10759
Squillero, Giovanni, et al. Applications of Evolutionary Computation - 20th European Conference, EvoApplications. Springer, 2017.
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2017 | Bachelorsthesis | LibreCat-ID: 3580
Hansmeier, Tim. An FPGA Accelerator for Checking Resolution Proofs. Universität Paderborn, 2017.
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2017 | Mastersthesis | LibreCat-ID: 74
Knorr, Christoph. OpenCL-basierte Videoverarbeitung auf heterogenen Rechenknoten. Universität Paderborn, 2017.
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2017 | Mastersthesis | LibreCat-ID: 10666
Riaz, Umair. Acceleration of Industrial Analytics Functions on a Platform FPGA. Paderborn University, 2017.
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2017 | Conference Paper | LibreCat-ID: 10630
Boschmann, Alexander, et al. “A Zynq-Based Dynamically Reconfigurable High Density Myoelectric Prosthesis Controller.” Design, Automation and Test in Europe (DATE), 2017, doi:10.23919/DATE.2017.7927137.
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2017 | Journal Article | LibreCat-ID: 10611
Anwer, Jahanzeb, and Marco Platzner. “Evaluating Fault-Tolerance of Redundant FPGA Structures Using Boolean Difference Calculus.” Microprocessors and Microsystems, Elsevier, 2017, pp. 160–72, doi:10.1016/j.micpro.2017.06.002.
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2017 | Conference Paper | LibreCat-ID: 10762
Kaufmann, Paul, and Roman Kalkreuth. “An Empirical Study on the Parametrization of Cartesian Genetic Programming.” Genetic and Evolutionary Computation (GECCO), Compendium, ACM, 2017, doi:10.1145/3067695.3075980.
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