Python(编程语言)
雅卡索引
计算机科学
背景(考古学)
分割
机器学习
人工智能
深度学习
模式识别(心理学)
地质学
操作系统
古生物学
作者
Joao Otavio Nascimento Firigato,José Marcato,Wesley Nunes Gonçalves,Vitor Matheus Bacani
出处
期刊:International Geoscience and Remote Sensing Symposium
日期:2021-07-11
标识
DOI:10.1109/igarss47720.2021.9554765
摘要
The potential of integrating deep learning and Google Earth Engine (GEE) is a few explored in the literature. Here, we investigated their potential in the context of Eucalyptus mapping in Brazilian Savanah. Based on GEE API using python language, it is possible to integrate it with Google Colab. The experiments were conducted using the U-Net semantic segmentation method. A total of 704, 88, and 88 patches were used for training, validation, and test, respectively. The overall accuracy obtained in the test dataset was 96.88%, while the Jaccard index was 0.84. These results demonstrated the applicability of these platforms for using deep learning techniques for mapping based on satellite images.
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