@inproceedings{3693b94acac2412d91352e73a5d58db2,
title = "The influence of SAR image quantization method on detection precision",
abstract = "In this paper, we combine deep learning with radar image processing to explore the influence of different quantization methods on the final detection performance of the radar image subjected to strong points after different quantification methods. Considering problems caused by the characteristics of SAR image data, the LeNet network model in deep learning was used to train and verify the quantified radar images respectively. The impact of different quantization methods on SAR image classification and detection was analyzed. The most friendly way to quantify the actual radar images was explored. Radar image target detection based on depth learning provides the basis for exploration.",
keywords = "Deep learning, Detection, Quantitative methods, SAR Image",
author = "Bing Sun and Zhixiong Zuo and Pengbo Wang",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 ; Conference date: 22-07-2018 Through 27-07-2018",
year = "2018",
month = oct,
day = "31",
doi = "10.1109/IGARSS.2018.8518783",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "33--36",
booktitle = "2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings",
address = "美国",
}