Abstract: Graph Neural Networks (GNNs) are rapidly becoming essential tools in deep learning, but their effectiveness when applied to images is often limited by challenges in graph representation.

Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...

Abstract: Aerial image classification plays a vital role in applications such as building footprint extraction, water/soil analysis, 3D reconstruction. Accurate classification enables timely ...

Abstract: In recent years, uncrewed aerial vehicle (UAV) technology has shown great potential for application in hyperspectral image (HSI) classification tasks due to its advantages of flexible ...

Scientists have captured the most complete, high-resolution map of the cold gas at the center of the Milky Way, which contains the raw material from which stars and planets are made. Information from ...

COLLIER COUNTY, Fla. — A local nonprofit is taking a significant step forward in addressing veteran homelessness in Collier County. Warrior Homes of Collier celebrated progress on its latest housing ...

Reps. Al Green and Christian Menefee will head to a Democratic primary runoff for Texas’ redrawn 18th District, according to a projection from CNN’s Decision Desk. Neither Green nor Menefee got more ...

(CNN) — State Rep. James Talarico will win the Democratic primary for US Senate in Texas, CNN’s Decision Desk projects, placing a once little-known state legislator at the top of the party’s ticket ...

Abstract: In this article, we propose a lightweight privacy-preserving convolutional neural network (LPP-CNN) framework for military vehicle image classification. Existing target classification ...

Abstract: Hyperspectral image (HSI) classification demands models that can jointly capture long-range spatial relations and high-dimensional spectral structures while remaining scalable to large ...