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20212024
most citedEarthNets: Empowering AI in Earth Observation

60 citations · 150 across the 17 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.CV2022★ 26 cited

SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation

Yi Wang, Nassim Ait Ali Braham, Zhitong Xiong +3

Self-supervised pre-training bears potential to generate expressive representations without human annotation. Most pre-training in Earth observation (EO) are based on ImageNet or m…

cs.CV2022★ 60 cited

EarthNets: Empowering AI in Earth Observation

Zhitong Xiong, Fahong Zhang, Yi Wang +2

Earth observation (EO), aiming at monitoring the state of planet Earth using remote sensing data, is critical for improving our daily lives and living environment. With a growing n…

cs.CV2022

Monitoring Urban Forests from Auto-Generated Segmentation Maps

Conrad M Albrecht, Chenying Liu, Yi Wang +2

We present and evaluate a weakly-supervised methodology to quantify the spatio-temporal distribution of urban forests based on remotely sensed data with close-to-zero human interac…

cs.CV2022★ 3 cited

Self-supervised Learning in Remote Sensing: A Review

Yi Wang, Conrad M Albrecht, Nassim Ait Ali Braham +2

In deep learning research, self-supervised learning (SSL) has received great attention triggering interest within both the computer vision and remote sensing communities. While the…

cs.CV2022★ 1 cited

Self-supervised Vision Transformers for Joint SAR-optical Representation Learning

Yi Wang, Conrad M Albrecht, Xiao Xiang Zhu

Self-supervised learning (SSL) has attracted much interest in remote sensing and earth observation due to its ability to learn task-agnostic representations without human annotatio…