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Semantic segmentation of remote sensing images with self-supervised multitask representation learning (JSTARS, 2021)
A generalizable and accessible approach to machine learning with global satellite imagery (Nature communications, 2021)
2022
Global and local contrastive self-supervised learning for semantic segmentation of HR remote sensing images (IEEE * Transactions on Geoscience and Remote Sensing, 2022)
SatMAE: Pre-training transformers for temporal and multi-spectral satellite imagery (NeurIPS, 2022)
An Empirical Study of Remote Sensing Pretraining (Transactions on Geoscience and Remote Sensing, 2022)
Timl: Task-informed meta-learning for agriculture (arxiv, 2022)
2023
CMID: A Unified Self-Supervised Learning Framework for Remote Sensing Image Understanding (IEEE Transactions on Geoscience and Remote Sensing, 2023)
SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation (IEEE Geoscience and Remote Sensing Magazine, 2023)
CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations (ICML, 2023)
Scale-MAE: A scale-aware masked autoencoder for multiscale geospatial representation learning (ICCV, 2023)
SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image Understanding (ICCV, 2023)
Cross-Scale MAE: A Tale of multi-scale Exploitation in Remote Sensing (NeurIPS, 2023)
GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization (NeurIPS, 2023)
SSL4EO-L: Datasets and Foundation Models for Landsat Imagery (NeurIPS Datasets and Benchmarks, 2023)
A Billion-scale Foundation Model for Remote Sensing Images (arxiv, 2023)
L* ightweight, Pre-trained Transformers for Remote Sensing Timeseries (arxiv, 2023)
Foundation Models for Generalist Geospatial Artificial Intelligence (arxiv, 2023)
USat: A Unified Self-Supervised Encoder for Multi-Sensor Satellite Imagery (arxiv, 2023)
DiffusionSat: A Generative Foundation Model for Satellite Imagery (arxiv, 2023)
SpectralGPT: Spectral Foundation Model (arxiv, 2023)
SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery (arxiv 2023)
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@calebrob6 has compiled this list of relevant AI for EO papers. Posting here and I'll try to keep it somewhat updated. Contributions welcomed!!! ❤️
Pre 2020
2021
2022
2023
L* ightweight, Pre-trained Transformers for Remote Sensing Timeseries (arxiv, 2023)
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