@inproceedings{6eed648d26c24f51bfbc943577beddfa,
title = "Software and Hardware Co-Design Method for Ship Detection in Remote Sensing Images",
abstract = "The on-board processing of ship target detection in remote sensing images can transmit the detection results directly back to the ground and obtain fast processing speed. However, the increase in the amount of remote sensing image data leads to the decrease in the timeliness of on-board remote sensing image ship detection. In this article, a software and hardware co-design method for target detection in remote sensing images is proposed. In this method, the processing system in Zynq system on chip (SoC) is used for pre-processing as well as integration and output of detection results, and the programmable logic in Zynq SoC is used for accelerating the MobileNetV3 target detection method. The experimental results show the proposed method can accomplish satisfying ship detection of remote sensing images. Meanwhile, the average processing time of a remote sensing image of 64 ∗ 64 size is 2.59 ms, which is a relatively fast processing speed.",
keywords = "accelerator, hardware and software co-design, on-board processing, ship detection",
author = "Tongrui Zhang and Wenyi Shao and Liansheng Liu and Fei Guo and Yu Peng",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 16th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2023 ; Conference date: 09-08-2023 Through 11-08-2023",
year = "2023",
doi = "10.1109/ICEMI59194.2023.10270093",
language = "英语",
series = "Proceedings of 2023 IEEE 16th International Conference on Electronic Measurement and Instruments, ICEMI 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "177--181",
editor = "Juan Wu and Jiali Yin",
booktitle = "Proceedings of 2023 IEEE 16th International Conference on Electronic Measurement and Instruments, ICEMI 2023",
address = "美国",
}