Like every other field, the field of remote sensing is undergoing one of the most transformative shifts in its history in this era of artificial ...

Table 1. Computational comparison of SR architectures. Additionally, computational overhead remains prohibitive for edge deployment. Existing efficient methods (Wang et al., 2024) require L sequential ...

The U.S. Naval Research Laboratory (NRL) launched a groundbreaking remote sensing experiment, Coastal Hyperspectral Reflectance Object Material Analysis (CHROMA), Sept. 4-19, 2025, designed to ...

In this graduate certificate, you will learn how to solve complex problems by integrating GeoAI technology with advanced AI and machine learning tools. You’ll be able to process and analyze large ...

Using seven decades of global research papers, NYU Tandon researchers found that China makes up 47% of publications in remote sensing — a science that uses specialized sensors to gather data from ...

1 School of Agriculture and Environmental Science, University of Southern Queensland, Toowoomba, Australia. 2 Irrigation and Water Management Division, Bangladesh Rice Research Institute (BRRI), ...

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Semantic segmentation of remote sensing images is pivotal for comprehensive Earth observation, but the demand for interpreting new object categories, coupled with the high expense of manual annotation ...

Abstract: Object detection is an important part of remote sensing image analysis to accurately identify key features in Earth observation data while minimizing resource usage. However, challenges such ...

Automated textual description of remote sensing images is essential for applications such as environmental monitoring, urban planning, and disaster management. However, most existing methods only ...