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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 ...

Lung diseases such as pneumonia, tuberculosis, COVID-19, and lung cancer remain significant global health challenges that demand rapid and accurate diagnosis to improve patient outcomes. This study proposes NASNet-ViT, a...

Brain–computer interfaces (BCIs) based on motor imagery (MI) provide a transformative direct communication pathway for patients with severe motor disabilities. However, the high inter-subject variability and non-statio...

Purpose: Dental caries is one of the most prevalent oral diseases worldwide, and predicting Early Enamel Caries (EEC) and Advanced Enamel Caries (AEC) in intraoral imaging is a significant clinical research challenge. To...

Power transformers are critical components of power systems, and their safe and reliable operation is essential for both industrial and residential applications. Real-time condition monitoring and early fault detection a...

Dynamic gesture recognition is a core technology for human–computer interaction, yet existing methods face prominent limitations in hand spatial topology modeling, long–short-term temporal feature fusion, and general...

Estimating three-dimensional morphological traits such as volume from two-dimensional RGB images presents inherent challenges due to the loss of depth information, projection distortions, and occlusions under field condi...

A novel mesh-free methodology for the coupled magnetic field-circuit simulation of power transformers is presented in this paper. The proposed methodology employs equivalent models for the conductors and the iron core, w...

Benign–malignant classification of pulmonary nodules from chest computed tomography (CT) is essential for early lung cancer screening and for reducing unnecessary biopsies and follow-up examinations, yet it remains cha...

This study aimed to evaluate the performance of deep learning models for segmenting the augmented bone following transalveolar sinus floor elevation (TSFE). Cone-beam computed tomography (CBCT) data from 103 patients und...

Objective: To generate synthetic Orthopantomograms (OPGs) using generative Artificial Intelligence (AI) models and to evaluate the realism of synthetic images through assessments by humans as well as AI models. Methodolo...

Introduction and aims: Oral and maxillofacial surgery (OMFS) produces complex clinical data, while artificial intelligence (AI) applications in this field remain limited despite great potential. This study aimed to map t...

Introduction and aims: Automated dental report generation faces significant challenges in multimodal fusion, often resulting in suboptimal semantic quality and risks of hallucination, where AI generates clinically unsupp...