@inproceedings{5b9c7fc6e2814d7e828a4ae27aaaa8dd,
title = "An End-to-End Practice of Remote Sensing Object Detection with NVIDIA Embedded System",
abstract = "This paper aims to develop an efficient method of remote sensing object detection with deep learning in an end-to-end manner. We proposed a method of region detection followed by target detection to detect small-scale targets from large-scale remote sensing images, with a light-weighted neural network trained on our own dataset. For a simulation of practical detection algorithm deployment, which requires both accuracy and efficiency on hardware of limited compute power, the whole algorithm was implemented and tested on NVIDIA Jetson AGX Xavier embedded platform.",
keywords = "CNN, embedded system, object detection, remote sensing",
author = "Jingyao Huang and Hao Su and Xun Liu and Wei Li and Yi Cai and Lingxue Wang",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021 ; Conference date: 28-05-2021 Through 31-05-2021",
year = "2021",
month = may,
day = "28",
doi = "10.1109/ICAIBD51990.2021.9458957",
language = "English",
series = "2021 4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "490--494",
booktitle = "2021 4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021",
address = "United States",
}