首页|LuoJiaAI:A cloud-based artificial intelligence platform for remote sensing image interpretation

LuoJiaAI:A cloud-based artificial intelligence platform for remote sensing image interpretation

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The rapid processing, analysis, and mining of remote-sensing big data based on intelligent interpretation technology using remote-sensing cloud computing platforms (RS-CCPs) have recently become a new trend. The existing RS-CCPs mainly focus on developing and optimizing high-performance data storage and intelligent computing for common visual representation, which ignores remote sensing data characteristics such as large image size, large-scale change, multiple data channels, and geographic knowledge embedding, thus impairing computational efficiency and accuracy. We construct a LuoJiaAI platform composed of a standard large-scale sample database (LuoJiaSET) and a dedicated deep learning framework (LuoJiaNET) to achieve state-of-the-art performance on five typical remote sensing interpretation tasks, including scene classification, object detection, land-use classification, change detection, and multi-view 3D reconstruction. The details of the LuoJiaAI application experiment can be found at the white paper for LuoJiaAI industrial application. In addition, LuoJiaAI is an open-source RSCCP that supports the latest Open Geospatial Consortium (OGC) standards for better developing and sharing Earth Artificial Intelligence (AI) algorithms and products on benchmark datasets. LuoJiaAI narrows the gap between the sample database and deep learning frameworks through a user-friendly data-framework collaboration mechanism, showing great potential in high-precision remote sensing mapping applications.

Artificial intelligencecloud computing platformremote-sensing intelligent interpretationsample databasedeep learning framework

Zhan Zhang、Mi Zhang、Jianya Gong、Xiangyun Hu、Hanjiang Xiong、Huan Zhou、Zhipeng Cao

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State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

Department of Land-Surveying and Geo-Informatics, Hong Kong Polytechnic University, Hong Kong, China

Chinese National Natural Science Foundation Projects国家自然科学基金重点项目Special Fund of Hubei Luojia Laboratory

4190126592038301220100028

2023

10.1080/10095020.2022.2162980

地球空间信息科学学报(英文版)
武汉大学（原武汉测绘科技大学）

地球空间信息科学学报(英文版)

CSCD
影响因子：0.207
ISSN：1009-5020
年,卷(期)：2023.26(2)
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