Self-supervised learning in remote sensing: A review
Y Wang, CM Albrecht, NAA Braham… - IEEE Geoscience and …, 2022 - ieeexplore.ieee.org
In deep learning research, self-supervised learning (SSL) has received great attention,
triggering interest within both the computer vision and remote sensing communities. While …
triggering interest within both the computer vision and remote sensing communities. While …
Object detection and image segmentation with deep learning on earth observation data: A review-part i: Evolution and recent trends
Deep learning (DL) has great influence on large parts of science and increasingly
established itself as an adaptive method for new challenges in the field of Earth observation …
established itself as an adaptive method for new challenges in the field of Earth observation …
Deep learning meets SAR: Concepts, models, pitfalls, and perspectives
Deep learning in remote sensing has received considerable international hype, but it is
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
mostly limited to the evaluation of optical data. Although deep learning has been introduced …
[HTML][HTML] The urban morphology on our planet–Global perspectives from space
Urbanization is the second largest mega-trend right after climate change. Accurate
measurements of urban morphological and demographic figures are at the core of many …
measurements of urban morphological and demographic figures are at the core of many …
Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …
investigating aggregated classes. The increase in data with a very high spatial resolution …
Self-supervised learning of remote sensing scene representations using contrastive multiview coding
In recent years self-supervised learning has emerged as a promising candidate for
unsupervised representation learning. In the visual domain its applications are mostly …
unsupervised representation learning. In the visual domain its applications are mostly …
Geo-bench: Toward foundation models for earth monitoring
Recent progress in self-supervision has shown that pre-training large neural networks on
vast amounts of unsupervised data can lead to substantial increases in generalization to …
vast amounts of unsupervised data can lead to substantial increases in generalization to …
Firerisk: A remote sensing dataset for fire risk assessment with benchmarks using supervised and self-supervised learning
In recent decades, wildfires have caused tremendous property losses, fatalities, and
extensive damage to forest ecosystems. Inspired by the abundance of publicly available …
extensive damage to forest ecosystems. Inspired by the abundance of publicly available …
On creating benchmark dataset for aerial image interpretation: Reviews, guidances, and million-aid
Y Long, GS ** as remote sensing scene classification using deep learning: A case study of metropolitan China
China, with the world's largest population, has gone through rapid development in the last
forty years and now has over 800 million urban citizens. Although urbanization leads to …
forty years and now has over 800 million urban citizens. Although urbanization leads to …