On the opportunities and challenges of foundation models for geospatial artificial intelligence
G Mai, W Huang, J Sun, S Song, D Mishra… - ar**_with_unsupervised_multi-modal_representation_learning_from_VHR_images_and_POIs/links/6569aa153fa26f66f4439837/Geographic-map**-with-unsupervised-multi-modal-representation-learning-from-VHR-images-and-POIs.pdf" data-clk="hl=nl&sa=T&oi=gga&ct=gga&cd=3&d=16152546633759592403&ei=D8GxZ7DlKdjGieoPr_Hp0AE" data-clk-atid="0w8sY5VfKeAJ" target="_blank">[PDF] researchgate.net
Geographic map** with unsupervised multi-modal representation learning from VHR images and POIs
Most supervised geographic map** methods with very-high-resolution (VHR) images are
designed for a specific task, leading to high label-dependency and inadequate task …
designed for a specific task, leading to high label-dependency and inadequate task …
On the opportunities and challenges of foundation models for geoai (vision paper)
Large pre-trained models, also known as foundation models (FMs), are trained in a task-
agnostic manner on large-scale data and can be adapted to a wide range of downstream …
agnostic manner on large-scale data and can be adapted to a wide range of downstream …
Multi-level urban street representation with street-view imagery and hybrid semantic graph
Street-view imagery has been densely covering cities. They provide a close-up perspective
of the urban physical environment, allowing a comprehensive perception and understanding …
of the urban physical environment, allowing a comprehensive perception and understanding …
Learning spatial interaction representation with heterogeneous graph convolutional networks for urban land-use inference
Urban land use is central to urban planning. With the emergence of urban big data and
advances in deep learning methods, several studies have leveraged graph convolutional …
advances in deep learning methods, several studies have leveraged graph convolutional …
Self-supervised Learning for Geospatial AI: A Survey
The proliferation of geospatial data in urban and territorial environments has significantly
facilitated the development of geospatial artificial intelligence (GeoAI) across various urban …
facilitated the development of geospatial artificial intelligence (GeoAI) across various urban …
City foundation models for learning general purpose representations from openstreetmap
Pre-trained Foundation Models (PFMs) have ushered in a paradigm-shift in AI, due to their
ability to learn general-purpose representations that can be readily employed in …
ability to learn general-purpose representations that can be readily employed in …
ReFound: Crafting a Foundation Model for Urban Region Understanding upon Language and Visual Foundations
Understanding urban regional characteristics is pivotal in driving critical insights for urban
planning and management. We have witnessed the successful application of pre-trained …
planning and management. We have witnessed the successful application of pre-trained …