用于作物制图的新型可迁移深度学习方法

IF 6 2区地球科学 Q1 GEOGRAPHY, PHYSICAL

GIScience & Remote Sensing Pub Date : 2024-08-27 DOI:10.1080/15481603.2024.2395700

Hongyan Che, Yaozhong Pan, Xingsheng Xia, Xiufang Zhu, Le Li, Yongsheng Huang, Xuechang Zheng, Lingang Wang

引用次数: 0

摘要

精确的作物测绘为政府决策和农业管理提供了重要信息。最近在深度学习方面取得的进展大大增强了...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A new transferable deep learning approach for crop mapping

Accurate crop mapping provides important information for government decision-making and agricultural management. Recent advancements in deep learning have significantly enhanced the capabilities of...

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来源期刊

GIScience & Remote Sensing 地学-遥感

CiteScore

11.20

自引率

9.00%

发文量

审稿时长

6 months

期刊介绍： GIScience & Remote Sensing publishes original, peer-reviewed articles associated with geographic information systems (GIS), remote sensing of the environment (including digital image processing), geocomputation, spatial data mining, and geographic environmental modelling. Papers reflecting both basic and applied research are published.