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Abstract In the world of the Internet of Things (IoT), wireless sensor networks (WSNs) play a vital role in enabling seamless communication between connected devices. In a WSN data prediction system based, clustering and...

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...

Abstract Large-scale mining equipment operates under extreme conditions, making accurate fault prediction and remaining useful life (RUL) estimation essential for predictive maintenance strategies. This paper proposes a ...

Abstract Prostate MRI segmentation is critical for accurate diagnosis and treatment planning but remains challenging due to the complex interplay between the peripheral zone’s thin, irregular boundaries and the central...

Abstract To investigate the effect of the Anterior Controllable Antedisplacement and Fusion (ACAF) procedure on stress within the spinal cord, nerve roots, and dura mater for different subtypes of cervical ossification o...

Abstract Medical picture categorization has been greatly enhanced by the use of deep learning, especially in the timely identification of skin lesions. Still, predictions from a single model remain unreliable due to thei...

Abstract Invasive water hyacinth threatens Lake Tana, Ethiopia—the source of the Blue Nile. This study presents the first comprehensive 11-year (2013–2024) remote sensing assessment of the water hyacinth invasion dyn...

Abstract A prompt and precise diagnosis is necessary to lessen the worldwide burden of asthma, a common chronic respiratory condition. Spirometry is one of the resource-intensive conventional methods that frequently misc...

Abstract Medical image segmentation is fundamental for delineating lesion and organ boundaries in clinical workflows. While UNet-based models remain widely used, CNN-dominant designs are limited in modeling long-range co...

Abstract Epilepsy is a chronic neurological disease that profoundly impacts patients’ daily lives. Electroencephalography (EEG) serves as a crucial tool for the clinical diagnosis of epilepsy and other brain disorders....

Abstract Lumbar spine disorders represent a significant public health concern, with accurate diagnosis relying on vertebral segmentation and quantification. Traditional methods, such as Cobb angle measurement are constra...

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 ...

Abstract Actions are the building blocks of our dynamic visual world, yet the neural computations supporting action perception are not well understood. How does perceptual and conceptual information unfold in the brain w...

Abstract DriveEmo-FL presents a privacy-preserving, radar-based emotion-recognition framework tailored for autonomous-vehicle (AV) cabins. Leveraging a compact embedded mmWave radar, the system captures upper-body emotio...

Abstract Multimodal industrial documents–such as operation manuals, circuit diagrams, and parameter tables–contain domain knowledge distributed across text, images, and document layout. However, most existing retriev...

Abstract The transformer architecture has demonstrated significant performance in image super-resolution (SR). However, for existing Transformer-based models, there are common drawbacks. They often fall short in local fe...

Abstract Accurate prediction of terrestrial water cycle variables like soil moisture (SM) and evapotranspiration (ET) is crucial, yet existing Deep Learning (DL) models face limitations. Many adopt Single-Task Learning (...

Abstract Glaucoma trabecular meshwork (GTM) cells cultured in vitro retain many characteristics of their in situ phenotype. Here, we used isobaric tandem mass tags (TMTpro) to label peptides from glaucomatous and non-gla...

Abstract Production safety and efficiency depends on the reliability of the critical components in industrial equipment. However, signals measured by sensors may have complicated nonlinear and long-term sequential dynami...

Abstract Human social behaviors involve complex interactions between individuals, and understanding how interbrain neural activity reflects and predicts these interactions is critical for advancing social cognitive neuro...