@inproceedings{cada54d630204c8f8fd6fcd912a618c0,
title = "Analysis of the Impact of Google Maps' Level on Object Detection",
abstract = "Remote sensing images have different levels based on spatial resolution, which will affect the object detection performance seriously. This paper quantitatively analyses the impact of Google Maps' level on object detection, taking the transmission tower as an example. The object area proportion (OAP) index is defined to help choose the data used for rapid detections and is capable of obtaining the optimal results under the particular requirements of speed and accuracy when observing a specific object in remote sensing images.",
keywords = "Google Maps, Object detection, convolutional neural network, map level",
author = "Bing Sun and Yi Xu and Chunsheng Li and Junfei Yu",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 ; Conference date: 28-07-2019 Through 02-08-2019",
year = "2019",
month = jul,
doi = "10.1109/IGARSS.2019.8898626",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1248--1251",
booktitle = "2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings",
address = "美国",
}