Real-Time Classification of Disaster Images from Social Media with a Self-Supervised Learning Framework-Reference-Cited by-同舟云学术

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Real-Time Classification of Disaster Images from Social Media with a Self-Supervised Learning Framework

Published:2022-07-17 Issue: Volume: Page:
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Container-title:IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Cai Tianhui¹,Gan Hongyu²,Peng Bo³,Huang Qunying³,Zou Zhiqiang²

Affiliation:

1. College of Liberal Arts & Sciences, University of Illinois at Urbana Champaign,Urbana,IL,USA

2. College of Computer, Nanjing University of Posts and Telecommunications,Jiangsu,China

3. University of Wisconsin - Madison,Department of Geography,Madison,WI,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9883023/9883024/09883129.pdf?arnumber=9883129

Reference11 articles.

1. Deep Residual Learning for Image Recognition

2. Momentum Contrast for Unsupervised Visual Representation Learning

3. MobileNetV2: Inverted Residuals and Linear Bottlenecks

4. CrisisMMD: Multimodel Twitter Datasets from Natural Disaster;alam;Proceedings of the 12th International AAAI Conference on Web and Social Media (ICWSM),2019

Cited by 2 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. Mobility-aware federated self-supervised learning in vehicular network;Urban Lifeline;2024-09-11

2. Synergizing Vision and Language in Remote Sensing: A Multimodal Approach for Enhanced Disaster Classification in Emergency Response Systems;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

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