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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...

Event-based image processing represents an emerging research field within computer vision and is gaining increasing relevance in modern imaging technologies. In contrast to conventional frame-based approaches, neuromorph...

ABSTRACT With the advancement of satellite remote sensing technology, object detection based on high‐resolution remote sensing imagery has emerged as a prominent research focus in the field of computer vision. Although...

To address the difficulty of blasthole detection during the charging phase of drill-and-blast tunnelling, which is aggravated by dust interference and insufficient illumination, this study proposes an intelligent blastho...

Objectives: Deep learning networks have achieved significant progress in caries diagnosis, but automated localization and numbering of carious teeth in cone-beam computed tomography (CBCT) images remain underexplored. Th...

The paper represents the experimental implementation of a Drone-based solar panel inspection using YOLOv8-based object detection with Ultraviolet sensing for automated and enhanced defect inspection. A quadcopter platfor...

Abstract Lameness in cattle is a significant welfare and economic concern. To address this, we developed an end-to-end deep learning framework for 24/7 lameness monitoring using top-down depth images of cattle. The frame...

ObjectiveIn recent years, the application of Deep Learning Reconstruction (DL Recon) technology in MRI has significantly improved the detection rate of small focal liver lesions (FLLs). This study aims to compare the det...

Hate speech is pervasive across most social media platforms, profoundly impacting users' lives and wellbeing. To address this critical issue, researchers are exploring explainable AI (XAI), which helps users understand A...

ObjectiveThis study aimed to conduct an exploratory observational analysis to assess the association between bacterial L-form detection and intrauterine infection in pregnant women with placenta previa and bleeding, and ...

Abstract BackgroundDepression affects more than 300 million people worldwide and is a leading contributor to the global disease burden. Traditional diagnostic methods, such as structured clinical interviews, ...

The rapid proliferation of unmanned aerial vehicles (UAVs) has created an urgent need for robust detection & identification systems to ensure airspace security and safety. However, the scarcity of large-scale, div...

Accurate identification of plant-parasitic nematodes is fundamental to effective crop protection and the maintenance of soil ecosystem integrity. This study integrates morphological characterization with deep learning-ba...

Abstract Intertidal macrobenthos are vital bioindicators of coastal ecosystem health due to their ecological roles, limited mobility, and sensitivity to environmental disturbances. However, traditional field‐based moni...

Peacocks have become a significant threat to agricultural fields, causing crop damage and affecting irrigation infrastructure. Traditional deterrence tools, such as scarecrows and nets, are often inefficient, labor- inte...

ABSTRACT To enable autonomous operations in complex industrial environments, this paper proposes retrieval‐augmented generation with large language models for robotic operations (RAGLRO), a robotic framework specifical...

IntroductionThe visual system must integrate spatially fragmented information to perceive coherent object boundaries. Contour integration represents a fundamental process underlying this perceptual organization by linkin...

Abstract Objective Klebsiella pneumoniae (Kp) is a clinically prevalent opportunistic pathogen, with escalating antimicrobial resistance posing substantial challenges. Current vaccine strategies are constrained by the...

Abstract Background The global expansion of Aedes aegypti and Aedes albopictus mosquitoes has intensified arboviral epidemics, generating annual socio-economic losses exceeding 2 billion US dollars, mainly in the America...

Background: The release of micro- and nanoplastics (MNPs) from tea bags during brewing is a significant, recently identified source of potential human exposure. This systematic review collected global research published ...

ObjectiveLimestone water hazards in coal seam floors represent one of the two primary categories of mine water hazards in China. Limestone aquifers are generally characterized by abundant static water reserves and consid...

Abstract Background Skin disorders are widespread, and there is increasing demand for reliable, standardized herbal therapeutics. Kumkumadi Tailam, a classical Ayurvedic polyherbal oil formulation, incorporates several b...

ObjectiveEarly recognition of inborn errors of immunity (IEI) is critical to avoid morbidity and irreversible organ damage. Jeffrey Modell Foundation (JMF) warning signs have long guided and still guide clinical suspicio...