Fetching the paper…
Reading the bibliography…
Self-supervised learning guided by masked image modelling, such as Masked AutoEncoder (MAE), has attracted wide attention for pretraining vision transformers in remote sensing.
“A computational approach to edge detection”
John Canny · 1986
Earlier work this paper cites.
“NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space”
Bo-Cai Gao · 1996
Earlier work this paper cites.
“On the relation between NDVI, fractional vegetation cover, and leaf area index”
Toby Carlson and David Ripley · 1997
Earlier work this paper cites.
“Using the Canny edge detector for feature extraction and enhancement of remote sensing images”
Mohamed Ali and David Clausi · 2001
Earlier work this paper cites.
“Use of normalized difference built-up index in automatically mapping urban areas from TM imagery”
Yong Zha, Jay Gao and Shaoxiang Ni · 2003
Earlier work this paper cites.
“Distinctive image features from scale-invariant keypoints”
David Lowe · 2004
Earlier work this paper cites.
“Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods”
H Liu and KC Jezek · 2004
Earlier work this paper cites.
“Histograms of oriented gradients for human detection”
Navneet Dalal and Bill Triggs · 2005
Earlier work this paper cites.
“Land-cover change detection using multi-temporal MODIS NDVI data”
Ross Lunetta et al · 2006
Earlier work this paper cites.
“The normalized difference vegetation index”
Nathalie Pettorelli · 2013
Earlier work this paper cites.
“Histograms of oriented gradients for landmine detection in ground-penetrating radar data”
Peter Torrione, Kenneth Morton, Rayn Sakaguchi and Leslie Collins · 2013
Earlier work this paper cites.
“SAR-SIFT: a SIFT-like algorithm for SAR images”
Flora Dellinger et al · 2014
Earlier work this paper cites.
“Remote sensing image registration with modified SIFT and enhanced feature matching”
Wenping Ma et al · 2016
Earlier work this paper cites.
“Google Earth Engine: Planetary-scale geospatial analysis for everyone”
Noel Gorelick et al · 2017
Cited alongside, same era.
“Decoupled Weight Decay Regularization”
Ilya Loshchilov and Frank Hutter · 2018
Cited alongside, same era.
“mixup: Beyond Empirical Risk Minimization”
Hongyi Zhang, Moustapha Cisse, Yann Dauphin and David Lopez-Paz · 2018
Cited alongside, same era.
“Unified perceptual parsing for scene understanding”
Tete Xiao et al · 2018
Cited alongside, same era.
“Tile2vec: Unsupervised representation learning for spatially distributed data”
Neal Jean et al · 2019
Cited alongside, same era.
“Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification”
Patrick Helber, Benjamin Bischke, Andreas Dengel and Damian Borth · 2019
Cited alongside, same era.
“Self-Supervised Learning in Remote Sensing: A Review”
Yi Wang et al · 2022
Later among the works it cites.
“Masked autoencoders are scalable vision learners”
Kaiming He et al · 2022
Later among the works it cites.
“Satmae: Pre-training transformers for temporal and multi-spectral satellite imagery”
Yezhen Cong et al · 2022
Later among the works it cites.
“Simmim: A simple framework for masked image modeling”
Zhenda Xie et al · 2022
Later among the works it cites.
“Masked feature prediction for self-supervised visual pre-training”
Chen Wei et al · 2022
Later among the works it cites.
“SatViT: Pretraining Transformers for Earth Observation”
Anthony Fuller, Koreen Millard and James Green · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”
Alexey Dosovitskiy et al · 2020
Cited alongside, same era.
“IEEE GRSS Data Fusion Contest”, 2020
Michael Schmitt et al · 2020
Cited alongside, same era.
“Generative pretraining from pixels”
Mark Chen et al · 2020
Cited alongside, same era.
“Kornia: an open source differentiable computer vision library for pytorch”
Edgar Riba et al · 2020
Cited alongside, same era.
“BigEarthNet-MM: A large-scale, multimodal, multilabel benchmark archive for remote sensing image classification and retrieval [software and data sets]”
Gencer Sumbul et al · 2021
Cited alongside, same era.
“BEiT: BERT Pre-Training of Image Transformers”
Hangbo Bao, Li Dong, Songhao Piao and Furu Wei · 2021
Cited alongside, same era.
“Ringmo: A remote sensing foundation model with masked image modeling”
Xian Sun et al · 2022
Later among the works it cites.
“Land Cover Classification for Polarimetric SAR Images Based on Vision Transformer”
Hongmiao Wang, Cheng Xing, Junjun Yin and Jian Yang · 2022
Later among the works it cites.
“Masked Auto-Encoding Spectral–Spatial Transformer for Hyperspectral Image Classification”
Damian Ibanez, Ruben Fernandez-Beltran, Filiberto Pla and Naoto Yokoya · 2022
Later among the works it cites.
“EarthNets: Empowering AI in Earth Observation”
Zhitong Xiong et al · 2022
Later among the works it cites.
“Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning”
Colorado Reed et al · 2023
Closest in time.
“SSL4EO-S12: A large-scale multimodal, multitemporal dataset for self-supervised learning in Earth observation”
Yi Wang et al · 2023
Closest in time.
“A billion-scale foundation model for remote sensing images”
Keumgang Cha, Junghoon Seo and Taekyung Lee · 2023
Closest in time.