TY - GEN
T1 - PYNQ FPGA Hardware implementation of LeNet-5-Based Traffic Sign Recognition Application
AU - Maraoui, Amna
AU - Messaoud, Seifeddine
AU - Bouaafia, Soulef
AU - Ammari, Ahmed Chiheb
AU - Khriji, Lazhar
AU - Machhout, Mohsen
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/3/22
Y1 - 2021/3/22
N2 - Computer Vision is one of the most flagship fields in the last decade. Meanwhile, embedded boards (FPGAs) represent the technological advancement trends by including software processor and programmable logic units at the same FPGA core. However, the fusion of the embedded system and computer vision provides the nascent embedded vision field. This domain occupied all areas, even future Industry 4.0, by exploiting them in control and management tasks. Otherwise, embedded vision with artificial intelligence plays an important role in many vital applications such as advanced driver-assistance systems Otherwise, embedded vision with artificial intelligence plays an important role in many vital applications such as advanced driver-assistance systems in smart transportation context. This paper falls within this range, by implementing LeNet-5 Model-based Traffic Sign Recognition application on Xilinx embedded FPGA system. Implementation results prove that our Co-design prototype, including Processing System (PS) and Programmable Logic (PL) parts, achieves best performance in terms of hardware cost and run-time execution.
AB - Computer Vision is one of the most flagship fields in the last decade. Meanwhile, embedded boards (FPGAs) represent the technological advancement trends by including software processor and programmable logic units at the same FPGA core. However, the fusion of the embedded system and computer vision provides the nascent embedded vision field. This domain occupied all areas, even future Industry 4.0, by exploiting them in control and management tasks. Otherwise, embedded vision with artificial intelligence plays an important role in many vital applications such as advanced driver-assistance systems Otherwise, embedded vision with artificial intelligence plays an important role in many vital applications such as advanced driver-assistance systems in smart transportation context. This paper falls within this range, by implementing LeNet-5 Model-based Traffic Sign Recognition application on Xilinx embedded FPGA system. Implementation results prove that our Co-design prototype, including Processing System (PS) and Programmable Logic (PL) parts, achieves best performance in terms of hardware cost and run-time execution.
KW - FPGA
KW - LeNet-5
KW - PYNQ
UR - http://www.scopus.com/inward/record.url?scp=85107470362&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85107470362&partnerID=8YFLogxK
U2 - 10.1109/SSD52085.2021.9429480
DO - 10.1109/SSD52085.2021.9429480
M3 - Conference contribution
AN - SCOPUS:85107470362
T3 - 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021
SP - 1004
EP - 1009
BT - 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021
Y2 - 22 March 2021 through 25 March 2021
ER -