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21 Publications


2023 | Book Chapter | LibreCat-ID: 45899 | OA
Boschmann, A., Clausing, L., Jentzsch, F., Ghasemzadeh Mohammadi, H., & Platzner, M. (2023). Flexible Industrial Analytics on Reconfigurable Systems-On-Chip. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, & H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412, pp. 225–236). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.5281/zenodo.8068713
LibreCat | Files available | DOI
 

2021 | Conference Paper | LibreCat-ID: 21610
Awais, M., Ghasemzadeh Mohammadi, H., & Platzner, M. (2021). LDAX: A Learning-based Fast Design Space Exploration Framework for Approximate Circuit Synthesis. In Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021 (pp. 27–32). Virtual: ACM. https://doi.org/10.1145/3453688.3461506
LibreCat | DOI
 

2021 | Conference Paper | LibreCat-ID: 30908
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. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. https://doi.org/10.1007/978-3-030-93736-2_27
LibreCat | DOI
 

2020 | Conference Paper | LibreCat-ID: 16213
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 | DOI
 

2020 | Conference Paper | LibreCat-ID: 20808
Ghasemzadeh Mohammadi, H., Arshad, R., Rautmare, S., Manjunatha, S., Kuschel, M., Jentzsch, F. P., Platzner, M., Boschmann, A., & Schollbach, D. (2020). DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms. 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). https://doi.org/10.1109/etfa46521.2020.9211880
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