EFFC-Net: lightweight fully convolutional neural networks in remote sensing disaster images-Reference-Cited by-同舟云学术

EFFC-Net: lightweight fully convolutional neural networks in remote sensing disaster images

Published:2023-05-17 Issue: Volume: Page:1-12
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Yuan Jianye¹^ORCID,Ma Xin²^ORCID,Zhang Zhentong³,Xu Qiang⁴,Han Ge⁵,Li Song¹,Gong Wei¹,Liu Fangyuan⁶,Cai Xin⁷

Affiliation:

1. School of Electronic Information, Wuhan University, Wuhan, China

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

3. School of Cyber Science and Engineering, Southeast University, Nanjing, China

4. Department of Electrical Engineering, and Center for Intelligent Multidimensional Data Analysis, City University of Hong Kong, Hong Kong, China

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

6. The Second Clinical Medical College, Jinan University, Shenzhen, China

7. School of Electrical Engineering, Xinjiang University, Urumqi, China

Funder

the National Natural Science Foundation of China

Research and Development

Wuhan University

Publisher

Informa UK Limited

Subject

Computers in Earth Sciences,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2023.2183145

Reference55 articles.

1. Characterization of focal EEG signals: A review

2. Agarap, A. F. 2018. “Deep Learning Using Rectified Linear Units (Relu).” arXiv preprint arXiv:1803.08375.

3. Alom, M. Z., Taha, T. M., Yakopcic, C., Westberg, S., Sidike, P., Nasrin, M. S., Van Esesn, et al. 2018. “The History Began from Alexnet: A Comprehensive Survey on Deep Learning Approaches.” arXiv preprint arXiv:1803.01164.

4. AswinGopinathan. 30 March 2021. Cyclone, wildfire, flood and Earthquake[eb/ol]. https://www.kaggle.com/aswin1871/cyclonewildfireflood-and-earthquake

Cited by 6 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. DiRecNetV2: A Transformer-Enhanced Network for Aerial Disaster Recognition;SN Computer Science;2024-08-08

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

3. A classification framework with multi-level fusion of object-based analysis and convolutional neural network: a case study for land use classification in mining areas;Geo-spatial Information Science;2024-04-25

4. Fine-grained ship image classification and detection based on a vision transformer and multi-grain feature vector FPN model;Geo-spatial Information Science;2024-04-16

5. A cross-stage features fusion network for building extraction from remote sensing images;Geo-spatial Information Science;2024-04-12