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Abstract Satellite Image Classification is a process in remote sensing that aims at classifying pixels of satellite imagery into usable information of land use and land cover. This information is not only limited to seve...

The need for early and precise identification of abnormalities has made the detection and classification of brain tumours essential components of medical diagnosis. Because brain tumours are naturally complex and can hav...

Scintillation-based X-ray imaging can provide convenient visual observation of absorption contrast by standard digital cameras, which is critical in a variety of science and engineering disciplines. More efficient scinti...

Coronal mass ejections (CMEs) are eruptions originating from the solar corona, usually carrying a large amount of fast-flowing plasma into interplanetary space, accompanied by an enhanced magnetic field. CMEs can form sh...

Recently, in the image super-resolution (SR) domain, Transformers have outperformed Convolution Neural Networks (CNNs) with reduced computational complexity and parameters by modeling long-range dependencies input-depend...

After an earthquake, numerous buildings are destroyed, and the frequency of structural collapses increases significantly in regions lacking comprehensive geophysical surveys. Furthermore, the number of deaths increases d...

INTRODUCTION: With the rapid growth of offshore wind power integration and increasing wind power penetration, accurate power forecasting has become essential for maintaining grid stability and supporting economic dispatc...

Accurate estimation of signal-to-noise ratio (SNR) in Scanning Electron Microscopy (SEM) is crucial because it evaluates the image quality. SEM images faced a challenge whereby Gaussian noise commonly appears in the imag...

Language classification systems are used to classify spoken language from a particular phoneme sample and are usually the first step of many spoken language processing tasks, such as automatic speech recognition (ASR) sy...

Abstract Graph Neural Networks have emerged as a powerful paradigm for artificial intelligence driven drug discovery, offering molecular representation learning that surpasses many conventional approaches. Traditional ex...

Airport planning depends to a large extent on the levels of activity that are anticipated. To plan the facilities and infrastructures of an airport system and to be able to satisfy future needs, it is essential to predic...

One of the deadliest diseases that can affect children and adults is a brain tumour. A brain tumour is the abnormal growth of cells in the brain or near it. Commonly, there are two types of tumours: malignant (cancerous)...

Plastic waste is a significant environmental concern, constituting a major portion of the global waste stream. Improper disposal and accumulation have led to severe environmental challenges, including pollution, harm to ...

Sleep plays an important role in physical health, cognition, and emotional well-being. Since sleep disorders can affect all these aspects, accurately detecting sleep stages is key to proper diagnosis and monitoring. Auto...

Plasmonic nanoantennas with suitable far-field characteristics are of huge interest for utilization in optical wireless links, inter-/intrachip communications, LiDARs, and photonic integrated circuits due to their except...

Graph-based text classification has become an effective paradigm for modeling corpus-level structure, particularly under limited supervision. However, most existing approaches rely on document–word representations...

The rapid growth and increasing complexity of Internet of Things (IoT) networks require efficient real-time monitoring and anomaly detection mechanisms. Traditional machine learning approaches often struggle to handle th...

The prediction and design of photonic features have traditionally been guided by theory-driven computational methods, spanning a wide range of direct solvers and optimization techniques. Motivated by enormous advances in...

We conduct a search for strong gravitational lenses in the Dark Energy Survey (DES) Year 6 imaging data. We implement a pre-trained Vision Transformer (ViT) for our machine learning (ML) architecture and adopt interactiv...

Over the past decade, mobile devices have become an integral part of our daily routines, offering a broad spectrum of applications that enhance everyday tasks. As more people adopt smartphones, developers are increasingl...

This study addresses the need to detect the severity of acne in skin care and beauty, particularly in managing the diagnosis of acne severity more efficiently and objectively. Acne, a common skin problem, can significant...

Abstract Background Knee osteoarthritis (OA) is a leading global cause of disability, yet conventional tools lack sensitivity for early detection and precise prognostication. Artificial intelligence (AI) and machine lear...

Diabetic retinopathy (DR) is one of the leading causes of preventable blindness worldwide, making timely and accurate detection crucial for effective management. This study introduces DR-NetFusion, a novel hybrid deep le...

The rapid proliferation of Internet of Medical Things (IoMT) devices in healthcare environments has created critical cybersecurity vulnerabilities that demand both accurate and interpretable intrusion detection solutions...