Hardware Acceleration of YOLO-based Convolutional Neural Network Detector by Deep Learning Processor Unit for Intelligent Autonomous Mover

Author:

Chen Kuan-Hung1,Wu Chung-Bin2,Hwang Yin-Tsung2,Chen Hua-Luen2,Lin Jie-Min2,Fan Chih-Peng2

Affiliation:

1. Feng Chia University,Department of Electronic Engineering,Taichung,Taiwan (R.O.C.)

2. National Chung Hsing University,Department of Electrical Engineering,Taichung,Taiwan (R.O.C.)

Publisher

IEEE

Reference6 articles.

1. YOLOv3: An Incremental Improvement;redmon,0

2. YOLO: Real-Time Object Detection,0

3. Acceleration Study of Two-Stage and Deep-Learning Based Facial Direction Detection on GPU-Based Edge Device

4. YOLOv4: Optimal Speed and Accuracy of Object Detection;bochkovskiy,0

5. DPU for Convolutional Neural Network,0

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. UML-Based Design Flow for Systems with Neural Networks;2023 38th Conference on Design of Circuits and Integrated Systems (DCIS);2023-11-15

2. Implementation of Convolutional Neural Networks on FPGA for Object Detection;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06

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