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Data-driven design approaches based on deep learning have been introduced in nanophotonics to reduce time-consuming iterative simulations, which have been a major challenge. Here, we report the first use of conditional d...

Autism spectrum disorder (ASD) is a neurodevelopmental disorder, which seriously affects children’s normal life. Screening potential autistic children before professional diagnose is helpful to early detection and earl...

We demonstrate transfer learning as a tool to improve the efficacy of training deep learning models based on residual neural networks (ResNets). Specifically, we examine its use for study of multi-scale electrically larg...

Abstract For a single-structure deep learning fault diagnosis model, its disadvantages are an insufficient feature extraction and weak fault classification capability. This paper proposes a multi-scale deep feature fusio...

Adaptive learning systems require effective mechanisms to model students’ evolving learning states and provide personalized learning path recommendations. Traditional rule-based approaches are limited in capturing...

Abstract The new energy vehicle plays a crucial role in green transportation, and the energy management strategy of hybrid power systems is essential for ensuring energy-efficient driving. This paper presents a state-of-...

Media sosial sebagai media informasi dan komunikasi mulai berkembang pesat sejak internet mudah diakses. Orang dengan mudah menyatakan pendapat, ekspresi, opini, dan informasi melalui tulisan pada media sosial. Opini ata...

With the rapid expansion of the digital music industry, streaming platforms are required to efficiently and accurately classify massive music collections to support personalized recommendation, content organization, and ...

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...

Cloud computing environments face persistent structural challenges in cost control, dynamic resource allocation, and security risk management, which traditional infrastructure approaches fail to address adequately. This ...

Introduction: The advancement of AI-assisted oral disease diagnosis critically relies on the availability of annotated, high-quality datasets and resilient deep learning architectures. Nevertheless, progress in this doma...

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)...

Abstract Deep learning (DL) is progressively popular as a viable alternative to traditional signal processing (SP) based methods for fault diagnosis. However, the lack of explainability makes DL-based fault diagnosis met...

The ripening stage of a fruit is a crucial determinant of its quality. Traditional assessment methods for fruit ripeness are often subjective, error-prone, and time-consuming. Therefore, numerous attempts are being made ...

Abstract The advancement of autonomous driving heavily relies on the ability to accurate lane lines detection. As deep learning and computer vision technologies evolve, a variety of deep learning-based methods for lane l...

IntroductionEarly and accurate diagnosis of skin cancer has a huge impact on the survival rate of patients and deep learning-based CNN and dermatologists' intelligence support can fasten the diagnosis not only within the...

Speaker recognition is one of the field topics widely used in the field of speech technology, many research works has been conducted and little progress has been made in the past five to six years, and due to the advance...

Abstract Alzheimer’s disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of accessible early diagnostic methods. Even though it has en...

Abstract The importance of fear level detection in affective computing using physiological signals has not been extensively explored. Accurately detecting fear responses facilitates real-time emotional monitoring and imp...

ABSTRACT Plant diseases are the cause of heavy losses of crop production and, therefore, a big contributor to food shortages. Identifying these diseases as early as possible is important to limit the negative effects tha...

Abstract Hydraulic systems have the characteristics of strong fault concealment, powerful nonlinear time-varying signals, and a complex vibration transmission mechanism; hence, diagnosis of these systems is a challenge. ...

Dear Readers,It gives me great pleasure to announce the fourth regular issue of 2026. In this issue, 6 papers by 25 authors from 6 countries - Colombia, Greece, Mexico, Republic of Serbia, South Africa, Türkiye ...

Traffic forecasting is crucial for intelligent transportation systems. It has experienced significant advancements thanks to the power of deep learning in capturing latent patterns of traffic data. However, recent deep-l...

Los sistemas tradicionales de odometría visual (VO), directos o basados en características visuales, son susceptibles de cometer errores de correspondencia entre imágenes. Además, las configuraciones monoculares sól...