On the opportunities and challenges of foundation models for geospatial artificial intelligence
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 …
Csp: Self-supervised contrastive spatial pre-training for geospatial-visual representations
Geo-tagged images are publicly available in large quantities, whereas labels such as object
classes are rather scarce and expensive to collect. Meanwhile, contrastive learning has …
classes are rather scarce and expensive to collect. Meanwhile, contrastive learning has …
Sphere2Vec: A general-purpose location representation learning over a spherical surface for large-scale geospatial predictions
Generating learning-friendly representations for points in space is a fundamental and long-
standing problem in machine learning. Recently, multi-scale encoding schemes (such as …
standing problem in machine learning. Recently, multi-scale encoding schemes (such as …
A five-year milestone: reflections on advances and limitations in GeoAI research
ABSTRACT The Annual Meeting of the American Association of Geographers (AAG) in 2023
marked a five-year milestone since the first Geospatial Artificial Intelligence (GeoAI) …
marked a five-year milestone since the first Geospatial Artificial Intelligence (GeoAI) …
AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiology
In this pioneering study, inspired by AutoGPT, the state-of-the-art open-source application
based on the GPT-4 large language model, we develop a novel tool called AD-AutoGPT …
based on the GPT-4 large language model, we develop a novel tool called AD-AutoGPT …
Exploring new frontiers in agricultural nlp: Investigating the potential of large language models for food applications
This paper explores new frontiers in agricultural natural language processing by
investigating the effectiveness of using food-related text corpora for pretraining transformer …
investigating the effectiveness of using food-related text corpora for pretraining transformer …
Explainable spatially explicit geospatial artificial intelligence in urban analytics
Geospatial artificial intelligence (GeoAI) is proliferating in urban analytics, where graph
neural networks (GNNs) have become one of the most popular methods in recent years …
neural networks (GNNs) have become one of the most popular methods in recent years …
CATS: Conditional Adversarial Trajectory Synthesis for privacy-preserving trajectory data publication using deep learning approaches
The prevalence of ubiquitous location-aware devices and mobile Internet enables us to
collect massive individual-level trajectory dataset from users. Such trajectory big data bring …
collect massive individual-level trajectory dataset from users. Such trajectory big data bring …
EVKG: An interlinked and interoperable electric vehicle knowledge graph for smart transportation system
Over the past decade, the electric vehicle (EV) industry has experienced unprecedented
growth and diversification, resulting in a complex ecosystem. To effectively manage this …
growth and diversification, resulting in a complex ecosystem. To effectively manage this …
GeoAI in urban analytics
We are writing this editorial piece at the peak of the current Artificial Intelligence
(AI)'spring'as generative models quickly cross the bridge from the confines of academic and …
(AI)'spring'as generative models quickly cross the bridge from the confines of academic and …