OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery

While the pretraining of Foundation Models (FMs) for remote sensing (RS) imagery is on the rise, models remain restricted to a few hundred million parameters. Scaling models to billions of parameters has been shown to yield unprecedented benefits including emergent abilities, but requires data scali...

Full description

Bibliographic Details

Published in:	arXiv.org
Main Authors:	Dias, Philipe, Tsaris, Aristeidis, Bowman, Jordan, Potnis, Abhishek, Arndt, Jacob, Yang, H Lexie, Dalton Lunga
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 25.10.2024
Subjects:	Best practice Computation High resolution Image classification Image resolution Image segmentation Object recognition Parameters Remote sensing Satellite imagery Scaling Semantic segmentation
ISSN:	2331-8422
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!