In recent years, the use of convolutional neural networks (CNNs) and graph convolutional
networks (GCNs) has significantly advanced hyperspectral image classification (HSIC) …

Diffusion models are increasingly favored over traditional approaches like generative
adversarial networks (GANs) and auto-regressive transformers due to their remarkable …

Introduction Advanced traffic monitoring systems face significant challenges in vehicle
detection and classification. Conventional methods often require substantial computational …

MRI imaging primarily focuses on the soft tissues of the human body, typically performed
prior to a patient's transfer to the surgical suite for a medical procedure. However, utilizing …

This paper investigates virtual reality (VR) technology which can increase the quality of
experience (QoE) on the graphics quality within the gaming environment. The graphics …

Hyperspectral image (HSI) data has a wide range of valuable spectral information for
numerous tasks. HSI data encounters challenges such as small training samples, scarcity …

As the Metaverse promises to revolutionize human interaction and digital life, the role of
edge computing emerges as a critical enabler. This paper presents a comprehensive survey …

Multimodal neuroimaging, combining data from different sources, has shown promise in the
classification of the Alzheimer's disease (AD) stage. Existing multimodal neuroimaging …

In clinical datasets, missing data often occur due to various reasons including non-response,
data corruption, and errors in data collection or processing. Such missing values can lead to …

The rapid adoption of Unmanned Aerial Vehicles (UAVs) in the construction industry has
revolutionized safety, surveying, quality monitoring, and maintenance assessment. UAVs …