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The provision of accurate and explainable captions and answers to visual questions about remote sensing images is essential in areas such as disaster management, land-use supervision, and military analysis, where system ...

Abstract Wearable sensor–based human activity recognition (HAR) is central to smart sport and health-monitoring applications, yet existing deep learning models often rely on ad hoc multimodal fusion and offer limited i...

Transformer is a vital equipment in the power system. If the transformer is damage, can cause the electrical distribution to the consumer will be disrupted. Therefore, it needs special maintenance the performance of the ...

Abstract Access to large, diverse biomedical datasets is critical for advancing medical research, yet privacy regulations severely restrict data sharing. We present an end-to-end framework for privacy-preserving health d...

En el presente trabajo se exponen los resultados del análisis de los procesos tafonómicos que actuaron sobre los materiales arqueofaunísticos del sitio Martínez 3, el cual se halla emplazado en el sector deprimido de...

Abstract Background Fetal hypoxia is a leading cause of neonatal morbidity and mortality. Cardiotocography (CTG) is widely used to predict fetal hypoxia during labor, but its interpretation remains suboptimal. Artificial...

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...

Abstract Reliable interpretation of clinical imaging requires integrating complementary evidence across modalities, yet most AI systems remain limited by single-modality analysis and poor generalization across institutio...

IntroductionBrain tumor lesions in MRI images are characterized by low contrast, indistinct boundaries, and irregular morphology, posing substantial challenges for automated detection. RT-DETR provides an end-to-end, NMS...

This paper introduces CONV_GBERT, a hybrid deep learning framework for robust sentiment classification. The model integrates the bidirectional contextual understanding of BERT, the generative capabilities of GPT, and the...

Abstract Carbon markets play a critical role in emission reduction and sustainable economic transition; however, carbon price series exhibit high volatility, nonlinear dynamics, and complex cross-feature interactions, ma...

This paper presents Prak, a forced alignment tool developed for Czech, with a focus on transparent modular design and phonetic accuracy. In addition to a rule-based pronunciation module and exception handling, Prak intro...

Abstract Recognizing tactical formations is a critical task in professional football performance analytics. However, existing methods often fail to capture the dynamic and continuously evolving nature of modern tactical ...

The research introduces a 12-pulse D-STATCOM model developed and simulated to address voltage sag mitigation and power quality enhancement in unbalanced distribution feeders. It tackles critical power quality problems su...

Strong gravitational lenses serve as powerful probes for cosmology and the mass distribution of galaxies. However, identifying these rare systems is often hindered by inaccurate localization and confusion with morphologi...

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...

Reducing embodied carbon in the built environment requires reliable methods to assess structural materials, particularly steel, one of the most carbon-intensive. While environmental product declarations (EPDs) provide st...

ABSTRACT Background and Aims Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), is transforming healthcare by enabling improved diagnosis, prognosis, and personalized treatments. How...

Abstract Machine-generated music (MGM) has become a groundbreaking innovation with wide-ranging applications, such as music therapy, personalised editing, and creative inspiration within the music industry. However, the ...

Abstract Facial Expression Recognition (FER) demonstrates significant value in practical scenarios such as intelligent human–computer interaction. However, conventional FER methods often struggle to balance performance...

In response to the unstable accuracy rate of fault location in distribution network lines and the significant impact of communication with distribution automation devices, the fault perception analysis of distribution ne...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

Nitrogen dioxide (NO2) is a critical air pollutant with significant environmental and human health impacts, yet global and long-term NO2 datasets with daily continuity and fine spatial resolution remain limited. In this ...

Artistic style transfer has long been possible with the advancements of convolution- and transformer-based neural networks. Most algorithms apply the artistic style transfer to the whole image, but individual users may o...