Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …

Abstract Time Series Forecasting has been an active area of research due to its many
applications ranging from network usage prediction, resource allocation, anomaly detection …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Frequency-domain monaural speech enhancement has been extensively studied for over
60 years, and a great number of methods have been proposed and applied to many …

The reliable identification of subsurface sedimentary structures (ie, geologic heterogeneity)
is critical in various earth and environmental sciences, petroleum reservoir engineering, and …

The crowd sensing technology can realize the sensing and computing of people, machines,
and environment in smart industrial IoT-based coal mine, which provides a solution for …

Terahertz ultra-massive MIMO (THz UM-MIMO) is envisioned as one of the key enablers of
6G wireless networks, for which channel estimation is highly challenging. Traditional …

This work aims to investigate the use of a recently proposed, attention-free, scalable state-
space model (SSM), Mamba, for the speech enhancement (SE) task. In particular, we …

Maximising the content of supplementary cementitious materials as a partial replacement for
Portland cement and using recycled concrete aggregates as a full or partial replacement for …

As the occurrence of Denial of Service and Distributed Denial of Service (DoS/DDoS)
attacks increases, the demand for effective defense mechanisms increases. Recognition of …