F-E3D: FPGA-based Acceleration of an Efficient 3D Convolutional Neural Network for Human Action Recognition

Author:

Fan Hongxiang,Luo Cheng,Zeng Chenglong,Ferianc Martin,Que Zhiqiang,Liu Shuanglong,Niu Xinyu,Luk Wayne

Publisher

IEEE

Cited by 40 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. Exploring Memory Access Techniques for Efficient FPGA based 3D CNN Accelerator Design;2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS);2024-04-22

2. Human Action Recognition Systems: A Review of the Trends and State-of-the-Art;IEEE Access;2024

3. fpgaHART: A Toolflow for Throughput-Oriented Acceleration of 3D CNNs for HAR onto FPGAs;2023 33rd International Conference on Field-Programmable Logic and Applications (FPL);2023-09-04

4. FMM-X3D: FPGA-Based Modeling and Mapping of X3D for Human Action Recognition;2023 IEEE 34th International Conference on Application-specific Systems, Architectures and Processors (ASAP);2023-07

5. Efficient abnormality detection using patch-based 3D convolution with recurrent model;Machine Vision and Applications;2023-05-25

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