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1 Ergebnisse
1
Design of a YOLO Model Accelerator Based on PYNQ Architectu..:
, In:
2022 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)
,
Wang, Lin
;
Ao, Tianyong
;
Fu, Le
... - p. 15-18 , 2022
Link:
https://doi.org/10.1109/MLISE57402.2022.00011
RT T1
2022 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)
: T1
Design of a YOLO Model Accelerator Based on PYNQ Architecture
UL https://suche.suub.uni-bremen.de/peid=ieee-9943084&Exemplar=1&LAN=DE A1 Wang, Lin A1 Ao, Tianyong A1 Fu, Le A1 Liu, Jian A1 Liu, Yang A1 Zhou, Yi YR 2022 K1 Power demand K1 Quantization (signal) K1 Convolution K1 Computational modeling K1 Pipelines K1 Object detection K1 Delays K1 FPGA K1 YOLO accelerator K1 object detection K1 low power consumption SP 15 OP 18 LK http://dx.doi.org/https://doi.org/10.1109/MLISE57402.2022.00011 DO https://doi.org/10.1109/MLISE57402.2022.00011 SF ELIB - SuUB Bremen
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