A YOLO v3-tiny FPGA Architecture using a Reconfigurable Hardware Accelerator for Real-time Region of Interest Detection

With the recent advances in the fields of machine learning, neural networks and deep-learning algorithms have become a prevalent subject of computer vision. Especially for tasks like object classification and detection Convolutional Neu-ronal Networks (CNNs) have surpassed the previous traditional a...

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Veröffentlicht in:	Proceedings (Euromicro Conference on Digital Systems Design) S. 84 - 92
Hauptverfasser:	Herrmann, Viktor, Knapheide, Justin, Steinert, Fritjof, Stabernack, Benno
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.08.2022
Schlagworte:	Classification algorithms Computational modeling Convolutional neural networks FPGA Hardware Object detection Real-time systems Throughput Video sequences YOLO
ISSN:	2771-2508
Online-Zugang:	Volltext
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