Ultra-low power operation and extreme energy efficiency are strong requirements for a number of high-growth application areas requiring near-sensor processing, including elaboration of biosignals. Parallel near-threshold computing is emerging as an a...
Using standard Floating-Point (FP) formats for computation leads to significant hardware overhead since these formats are over-designed for error-resilient workloads such as iterative algorithms. Hence, hardware FP Unit (FPU) architectures need run-t...
This article describes a software environment called HybroGen, which helps to experiment binary code generation at run time. As computing architectures are getting more complex, the application performance is becoming data-dependent. The proposed exp...
The change detection of urban buildings is currently a hotspot in the research area of remote sensing, which plays a vital role in urban planning, disaster assessments and surface dynamic monitoring. SAR images have unique characteristics compared wi...
As interest in point cloud processing has gradually increased in the industry, point cloud sampling techniques have been researched to improve deep learning networks. As many conventional models use point clouds directly, the consideration of computa...
To improve the accuracy and efficiency of road crack detection, this paper proposes an enhanced model based on You Only Look Once version 8 (YOLOv8). The Cross Stage Partial DarkNet (CSPDarkNet) backbone network is replaced with TransXNet, which inte...
Small-object detection is a challenging task in computer vision due to the limited training samples and low-quality images. Transfer learning, which transfers the knowledge learned from a large dataset to a small dataset, is a popular method for impr...
Medical image segmentation presents substantial challenges arising from the diverse scales and morphological complexities of target anatomical structures. Although existing Transformer-based models excel at capturing global dependencies, they encount...
Computed tomography (CT) scan is a widely used, non-invasive, sensor-based imaging technique that provides critical intracranial information for rapid stroke assessment. Accurate segmentation of intracerebral hemorrhage (ICH) in sensor-derived CT ima...
Farmland shelterbelts are crucial elements in safeguarding agricultural ecological security and sustainable development, with their precise extraction being vital for regional ecological monitoring and precision agriculture management. However, const...
Cardiac computed tomography (CCT) has emerged as a central imaging modality in the workflow for left atrial appendage occlusion (LAAO), as accurate anatomical assessment is vital for successful intervention. CCT provides superior three-dimensional (3...
This study proposes a Swin-ReshoUnet architecture with a three-level enhancement mechanism to address inefficiencies in multi-scale feature extraction and gradient degradation in deep networks for high-precision seismic exploration. The encoder uses...
Platinum-based drugs play a pivotal role in contemporary cancer treatment, but their therapeutic utility is often limited by acquired resistance. The diiodido analog, cis-[PtI2(NH3)2] is a promising derivative that has demonstrated the ability to ove...
Pancreas segmentation in computed tomography (CT) images remains a challenging task due to the organ’s variable shape, size, and low contrast against surrounding tissues. In this study, we propose a two-stage pancreas segmentation framework tha...
In magnetic resonance imaging (MRI) segmentation, conventional approaches utilize U-Net models with encoder–decoder structures, segmentation models using vision transformers, or models that combine a vision transformer with an encoder–dec...
The gas chromatography–mass spectrometry (GC-MS) approach is established for the simultaneous determination of fenchone (FCO) and trans-anethole (TOH) in the essential oils and methanolic extracts of fennel (Foeniculum vulgare Mill.) fruits obt...
With the rapid advancements in computer vision and deep learning, multi-view stereo (MVS) based on conventional RGB cameras has emerged as a promising and cost-effective tool for botanical research. However, existing methods often struggle to capture...
Pneumonia, a prevalent respiratory infection, remains a leading cause of morbidity and mortality worldwide, particularly among vulnerable populations. Chest X-rays serve as a primary tool for pneumonia detection; however, variations in imaging condit...
Estimating bone age is essential for accurate diagnoses, appropriate care based on biological age, and fairness in legal matters. In the Indian medicolegal context, determining age through a clinical approach involves analyzing multiple joints; howev...
Manual labeling of lesions in medical image analysis presents a significant challenge due to its labor-intensive and inefficient nature, which ultimately strains essential medical resources and impedes the advancement of computer-aided diagnosis. Thi...
Interrupted and multi-source track segment association (TSA) are two key challenges in target trajectory research within radar data processing. Traditional methods often rely on simplistic assumptions about target motion and statistical techniques fo...
Chest X-ray (CXR) images can be used to diagnose a variety of lung diseases, such as tuberculosis, pneumonia, and lung cancer. However, the variation in lung morphology due to differences in age, gender, and the severity of pathology makes high-preci...
Complexes displaying multiple bonds between different metal atoms have considerable synthetic potential because of the combination of the high electronic and coordinative unsaturation associated to multiple bonds with the intrinsic polarity of hetero...
Graf-method ultrasound supports early assessment of developmental dysplasia of the hip (DDH). This study assessed a sequential artificial-intelligence-assisted workflow and clinicians’ Checklist I decisions with and without computer-aided diagn...
As autonomous driving systems shift from experimental testing environments to real-world open-road deployment, object detection in traffic scenes has emerged as a critical challenge in the perception pipeline. In complex traffic scenarios, significan...
Background: As advanced technology continues to evolve, incorporating robotics into surgical procedures has become imperative for precision and accuracy in preoperative planning. Nevertheless, the integration of three-dimensional (3D) imaging into th...
Effective welfare monitoring in laying hens is increasingly challenged by growing flock sizes, declining farm numbers, and the practical limitations of assessor-based protocols under commercial conditions. Precision Livestock Farming (PLF) technologi...