Over the past decade, Unmanned Aerial Vehicles (UAVs) have provided pervasive, efficient,
and cost-effective solutions for data collection and communications. Their excellent mobility …

Space-air-ground integrated networks (SAGINs) are key elements for facilitating high-speed
seamless connectivity to the devices/users in infrastructure-less environments, where the …

Abstract Recent advancements in Large Vision-Language Models (VLMs) have shown great
promise in natural image domains allowing users to hold a dialogue about given visual …

This study evaluates the performance of convolutional neural networks for semantic
segmentation of water bodies in very high-resolution satellite and aerial images from …

Open-vocabulary semantic segmentation presents the challenge of labeling each pixel
within an image based on a wide range of text descriptions. In this work we introduce a …

Modeling weather and climate is an essential endeavor to understand the near-and long-
term impacts of climate change, as well as to inform technology and policymaking for …

While semantic segmentation has seen tremendous improvements in the past, there are still
significant labeling efforts necessary and the problem of limited generalization to classes …

Traditional approaches for visual perception and evaluation of river landscapes adopt on-
site surveys or assessments through photographs. The former is expensive, hindering large …

Natural scene analysis and remote sensing imagery offer immense potential for
advancements in large-scale language-guided context-aware data utilization. This potential …

A vital and rapidly growing application, remote sensing offers vast yet sparsely labeled,
spatially aligned multimodal data; this makes self-supervised learning algorithms invaluable …