ABSTRACT: Accurate identification of seismic faults is critical to seismology, geological modeling, and disaster assessment. Traditional manual interpretation entails heavy reliance on domain ...

Abstract: This paper addresses the broadcast scheduling problem in multi-hop wireless sensor networks, a critical challenge that affects the efficiency and reliability of various network operations.

Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...

Automatic classification of interior decoration styles has great potential to guide and streamline the design process. Despite recent advancements, it remains challenging to construct an accurate ...

ABSTRACT: Government procurement contracts can be complicated, with extensive risk analysis and compliance reviews. The traditional methods of contract analytics are time-consuming and often inexact, ...

Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang, District 1, Ho Chi Minh City 700000, Vietnam ...

Abstract: In this paper, to explore the application of depression EEG data in semi-supervised classification, we designed an improved semi-supervised graph convolutional neural network model for ...

Large-scale semi-supervised annotation (self-learning, co-training) for text (code for papers @ KDD17, @ KAIS19); Repository maintained by Vasileios Iosifidis.