Abstract: Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on ...

Abstract: The rise of mpox as a global health concern highlights the necessity of effective early detection strategies to manage its propagation. Though less fatal than COVID-19, mpox poses some ...

Abstract: In the era of information explosion, clustering analysis of graph-structured data and empty graph-structured data is of great significance for extracting the intrinsic value of data. From ...

Efficient transmission of 3D point cloud data is critical for advanced perception in centralized and decentralized multi-agent robotic systems, especially nowadays with the growing reliance on edge ...

Jan 5 (Reuters) - Retired Harvard Law professor Alan Dershowitz has asked the U.S. Supreme Court to take up his lawsuit against CNN over its reporting on his defense of President Donald Trump, in a ...

Abstract: Short text classification is one of the core tasks in the field of natural language processing, which has attracted extensive attention due to problems such as semantic sparsity and ...

Abstract: Convolutional neural networks (CNNs) are widely adopted for remote sensing image scene classification. However, labeling of large annotated remote sensing datasets is costly and time ...

Abstract: Deep learning has emerged as a critical paradigm in hyperspectral image (HSI) classification, addressing the inherent challenges posed by high-dimensional data and limited labeled samples.

In 1992 the QE2 ran aground on a shoal that should have been safely below her keel. This analysis explains under keel clearance, outdated chart data, and the physics of squat that made deep water ...

Abstract: NLP, an AI field, that allows communication between computers and humans. NLP news text classification uses machine learning to categorize news into predefined groups. The vast volume of ...