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DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms. <i>2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)</i>. <a href=\"https://doi.org/10.1109/etfa46521.2020.9211880\">https://doi.org/10.1109/etfa46521.2020.9211880</a>","mla":"Ghasemzadeh Mohammadi, Hassan, et al. “DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms.” <i>2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)</i>, 2020, doi:<a href=\"https://doi.org/10.1109/etfa46521.2020.9211880\">10.1109/etfa46521.2020.9211880</a>.","bibtex":"@inproceedings{Ghasemzadeh Mohammadi_Arshad_Rautmare_Manjunatha_Kuschel_Jentzsch_Platzner_Boschmann_Schollbach_2020, title={DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms}, DOI={<a href=\"https://doi.org/10.1109/etfa46521.2020.9211880\">10.1109/etfa46521.2020.9211880</a>}, booktitle={2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)}, author={Ghasemzadeh Mohammadi, Hassan and Arshad, Rahil and Rautmare, Sneha and Manjunatha, Suraj and Kuschel, Maurice and Jentzsch, Felix Paul and Platzner, Marco and Boschmann, Alexander and Schollbach, Dirk}, year={2020} }","short":"H. Ghasemzadeh Mohammadi, R. Arshad, S. Rautmare, S. Manjunatha, M. Kuschel, F.P. Jentzsch, M. Platzner, A. Boschmann, D. Schollbach, in: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2020.","chicago":"Ghasemzadeh Mohammadi, Hassan, Rahil Arshad, Sneha Rautmare, Suraj Manjunatha, Maurice Kuschel, Felix Paul Jentzsch, Marco Platzner, Alexander Boschmann, and Dirk Schollbach. “DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms.” In <i>2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)</i>, 2020. <a href=\"https://doi.org/10.1109/etfa46521.2020.9211880\">https://doi.org/10.1109/etfa46521.2020.9211880</a>.","ieee":"H. Ghasemzadeh Mohammadi <i>et al.</i>, “DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms,” 2020, doi: <a href=\"https://doi.org/10.1109/etfa46521.2020.9211880\">10.1109/etfa46521.2020.9211880</a>."},"year":"2020","publication_identifier":{"isbn":["9781728189567"]},"publication_status":"published","doi":"10.1109/etfa46521.2020.9211880","title":"DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms","author":[{"id":"61186","full_name":"Ghasemzadeh Mohammadi, Hassan","last_name":"Ghasemzadeh Mohammadi","first_name":"Hassan"},{"full_name":"Arshad, Rahil","last_name":"Arshad","first_name":"Rahil"},{"first_name":"Sneha","last_name":"Rautmare","full_name":"Rautmare, Sneha"},{"first_name":"Suraj","last_name":"Manjunatha","full_name":"Manjunatha, Suraj"},{"full_name":"Kuschel, Maurice","last_name":"Kuschel","first_name":"Maurice"},{"first_name":"Felix Paul","full_name":"Jentzsch, Felix Paul","last_name":"Jentzsch"},{"last_name":"Platzner","id":"398","full_name":"Platzner, Marco","first_name":"Marco"},{"first_name":"Alexander","full_name":"Boschmann, Alexander","last_name":"Boschmann"},{"first_name":"Dirk","last_name":"Schollbach","full_name":"Schollbach, Dirk"}],"date_created":"2020-12-21T10:03:49Z","date_updated":"2023-07-09T13:08:07Z"},{"title":"Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture","supervisor":[{"first_name":"Christian","full_name":"Lienen, Christian","id":"60323","last_name":"Lienen"},{"first_name":"Marco","id":"398","full_name":"Platzner, Marco","last_name":"Platzner"},{"first_name":"Christian","orcid":"0000-0001-5728-9982","last_name":"Plessl","full_name":"Plessl, Christian","id":"16153"}],"date_created":"2021-03-10T07:09:14Z","author":[{"full_name":"Jentzsch, Felix P.","last_name":"Jentzsch","first_name":"Felix P."}],"date_updated":"2023-07-09T17:12:52Z","citation":{"apa":"Jentzsch, F. P. (2020). <i>Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture</i>.","short":"F.P. Jentzsch, Design and Implementation of a ReconOS-Based TensorFlow Lite Delegate Architecture, 2020.","bibtex":"@book{Jentzsch_2020, title={Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture}, author={Jentzsch, Felix P.}, year={2020} }","mla":"Jentzsch, Felix P. <i>Design and Implementation of a ReconOS-Based TensorFlow Lite Delegate Architecture</i>. 2020.","ama":"Jentzsch FP. <i>Design and Implementation of a ReconOS-Based TensorFlow Lite Delegate Architecture</i>.; 2020.","ieee":"F. P. Jentzsch, <i>Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture</i>. 2020.","chicago":"Jentzsch, Felix P. <i>Design and Implementation of a ReconOS-Based TensorFlow Lite Delegate Architecture</i>, 2020."},"year":"2020","language":[{"iso":"eng"}],"department":[{"_id":"78"}],"user_id":"398","_id":"21433","project":[{"grant_number":"160364472","_id":"1","name":"SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten "},{"name":"SFB 901 - T: SFB 901 - Project Area T","_id":"82"},{"_id":"83","name":"SFB 901 - T1: SFB 901 -Subproject T1"}],"status":"public","abstract":[{"text":"Modern machine learning (ML) techniques continue to move into the embedded system space because traditional centralized compute resources do not suit certain application domains, for example in mobile or real-time environments. Google’s TensorFlow Lite (TFLite) framework supports this shift from cloud to edge computing and makes ML inference accessible on resource-constrained devices. While it offers the possibility to partially delegate computation to hardware accelerators, there is no such “delegate” available to utilize the promising characteristics of reconfigurable hardware.\r\nThis thesis incorporates modern platform FPGAs into TFLite by implementing a modular delegate framework, which allows accelerators within the programmable logic to take over the execution of neural network layers. To facilitate the necessary hardware/software codesign, the FPGA delegate is based on the operating system for reconfigurable\r\ncomputing (ReconOS), whose partial reconfiguration support enables the instantiation of model-tailored accelerator architectures. In the hardware back-end, a streaming-based prototype accelerator for the MobileNet model family showcases the working order of the platform, but falls short of the desired performance. Thus, it indicates the need for further exploration of alternative accelerator designs, which the delegate could automatically synthesize to meet a model’s demands.","lang":"eng"}],"type":"mastersthesis"},{"citation":{"ama":"Lienen C. <i>Implementing a Real-Time System on a Platform FPGA Operated with ReconOS</i>. Universität Paderborn","ieee":"C. Lienen, <i>Implementing a Real-time System on a Platform FPGA operated with ReconOS</i>. Universität Paderborn.","chicago":"Lienen, Christian. <i>Implementing a Real-Time System on a Platform FPGA Operated with ReconOS</i>. Universität Paderborn, n.d.","apa":"Lienen, C. (n.d.). <i>Implementing a Real-time System on a Platform FPGA operated with ReconOS</i>. Universität Paderborn.","short":"C. Lienen, Implementing a Real-Time System on a Platform FPGA Operated with ReconOS, Universität Paderborn, n.d.","bibtex":"@book{Lienen, title={Implementing a Real-time System on a Platform FPGA operated with ReconOS}, publisher={Universität Paderborn}, author={Lienen, Christian} }","mla":"Lienen, Christian. <i>Implementing a Real-Time System on a Platform FPGA Operated with ReconOS</i>. Universität Paderborn."},"year":"2019","has_accepted_license":"1","publication_status":"submitted","title":"Implementing a Real-time System on a Platform FPGA operated with ReconOS","supervisor":[{"first_name":"Lennart","full_name":"Clausing, Lennart","id":"74287","orcid":"0000-0003-3789-6034","last_name":"Clausing"},{"id":"398","full_name":"Platzner, Marco","last_name":"Platzner","first_name":"Marco"},{"orcid":"0000-0002-3717-3939","last_name":"Hellebrand","full_name":"Hellebrand, Sybille","id":"209","first_name":"Sybille"}],"date_created":"2020-02-11T10:22:06Z","author":[{"last_name":"Lienen","full_name":"Lienen, Christian","id":"60323","first_name":"Christian"}],"date_updated":"2023-07-31T11:58:50Z","publisher":"Universität Paderborn","oa":"1","status":"public","file":[{"relation":"main_file","content_type":"application/pdf","file_size":5920668,"file_id":"17351","access_level":"open_access","file_name":"thesis_main.pdf","date_updated":"2021-02-13T16:46:58Z","date_created":"2020-07-01T11:46:49Z","creator":"clienen"}],"type":"mastersthesis","language":[{"iso":"eng"}],"file_date_updated":"2021-02-13T16:46:58Z","ddc":["004"],"department":[{"_id":"78"}],"user_id":"60323","_id":"15874","project":[{"_id":"83","name":"SFB 901 - T1: SFB 901 -Subproject T1"},{"_id":"82","name":"SFB 901 - T: SFB 901 - Project Area T"},{"name":"SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ","_id":"1","grant_number":"160364472"}]}]