LuoJiaAI: A cloud-based artificial intelligence platform for remote sensing image interpretation-Reference-Cited by-同舟云学术

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

Published:2023-02-23 Issue:2 Volume:26 Page:218-241
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Zhang Zhan¹^ORCID,Zhang Mi²^ORCID,Gong Jianya²,Hu Xiangyun²,Xiong Hanjiang¹,Zhou Huan³,Cao Zhipeng²

Affiliation:

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

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

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

Funder

the Chinese National Natural Science Foundation Projects

Major Program of the National Natural Science Foundation of China

Special Fund of Hubei Luojia Laboratory

Publisher

Informa UK Limited

Subject

Computers in Earth Sciences,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2022.2162980

Reference85 articles.

1. Abadi, M., A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, and M. Devin. 2016. “Tensorflow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.” arXiv preprint arXiv:1603.04467.

2. Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

3. Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review

4. Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

5. Canopy near-infrared reflectance and terrestrial photosynthesis

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An open flame and smoke detection dataset for deep learning in remote sensing based fire detection;Geo-spatial Information Science;2024-06-05

2. Vegetation classification in a subtropical region with Sentinel-2 time series data and deep learning;Geo-spatial Information Science;2024-05

3. How well do the volunteers label land cover types in manual interpretation of remote sensing imagery?;International Journal of Digital Earth;2024-04-30

4. T-UNet: triplet UNet for change detection in high-resolution remote sensing images;Geo-spatial Information Science;2024-04-17

5. On China’s earth observation system: mission, vision and application;Geo-spatial Information Science;2024-04-12