G Mai, N Lao, Y He, J Song… - … Conference on Machine …, 2023 - proceedings.mlr.press
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 …
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 …
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) …
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 …
This paper explores new frontiers in agricultural natural language processing by investigating the effectiveness of using food-related text corpora for pretraining transformer …
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 …
J Rao, S Gao, S Zhu - International Journal of Geographical …, 2023 - Taylor & Francis
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 …
Y Qi, G Mai, R Zhu, M Zhang - Transactions in GIS, 2023 - Wiley Online Library
Over the past decade, the electric vehicle (EV) industry has experienced unprecedented growth and diversification, resulting in a complex ecosystem. To effectively manage this …
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 …