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A Self-Adaptive Traffic Signal System Integrating Real-Time Vehicle Detection and License Plate Recognition for Enhanced Traffic Management

Manar Ashkanani, Alanoud AlAjmi, Aeshah Alhayyan, Zahraa Esmael et al. • Inventions (2025)

Traffic management systems play a crucial role in smart cities, especially because increasing urban populations lead to higher traffic volumes on roads. This results in increased congestion at intersections, causing delays and traffic viola...

DOAJ Open Access (DOAJ) DOI: 10.3390/inventions10010014

A Survey on Underwater Computer Vision

Salma González-Sabbagh, Antonio Robles‐Kelly • ACM Computing Surveys (2023)

Underwater computer vision has attracted increasing attention in the research community due to the recent advances in underwater platforms such as of rovers, gliders, autonomous underwater vehicles (AUVs) , and the like, that now make possi...

OPENALEX other-oa DOI: https://doi.org/10.1145/3578516

SnowMapPy: An automated GEE Python tool for snow cover mapping and monitoring in the Moroccan Atlas Mountains

Haytam Elyoussfi, Hatim Bechri, Mostafa Bousbaa, Salwa Belaqziz et al. • SoftwareX (2026)

SnowMapPy is an open-source Python-based package developed to streamline the collection, processing, and analysis of MODIS snow cover data from Terra and Aqua satellites. By automating essential steps, including data clipping, reprojection,...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.softx.2026.103006

Automatic building detection and land use classification in urban areas using multispectral high-spatial resolution imagery and LiDAR data

Txomin Hermosilla • ELCVIA Electronic Letters on Computer Vision and Image Analysis (2014)

Urban areas areimportant environments, accounting for approximately half the population of theworld. Cities attract residents partly because they offer ample opportunitiesfor development, which often results in urban sprawl and its complex ...

DOAJ Open Access (DOAJ) DOI: 10.5565/rev/elcvia.584

A Deep Learning-Driven Computer Vision and Web-Based Monitoring System for Automated Nutrient Management in Soilless Agriculture

Eda Nur Urtekin, Emre Dandıl • Journal of Agricultural Sciences (2026)

Sustainable food production increasingly relies on intelligent automation technologies that optimize resource usage while maintaining crop health. This study presents a deep learning-driven computer vision and web based monitoring system de...

DOAJ Open Access (DOAJ) DOI: 10.15832/ankutbd.1817471

Monitoring the spread of a pathogenic insect on vineyards using UAS

V. Longhi, A. Martino, A. M. Lingua, P. F. Maschio et al. • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2024)

Globalisation has contributed to rapid economic growth but has also exposed vulnerabilities such as the spread of pests in agriculture. An example is the Popillia Japonica Newman beetle, introduced to Italy in 2014, which has caused signifi...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLVIII-1-2024-443-2024

Unmanned Aerial Vehicle-Based Structural Health Monitoring and Computer Vision-Aided Procedure for Seismic Safety Measures of Linear Infrastructures

Luna Ngeljaratan, Elif Ecem Bas, Mohamed A. Moustafa • Sensors (2024)

Computer vision in the structural health monitoring (SHM) field has become popular, especially for processing unmanned aerial vehicle (UAV) data, but still has limitations both in experimental testing and in practical applications. Prior wo...

DOAJ Open Access (DOAJ) DOI: 10.3390/s24051450

Enabling scalable inspection of offshore mooring systems using cost-effective autonomous underwater drones

Dong Trong Nguyen, Christian Lindahl Elseth, Jakob Rude Øvstaas, Nikolai Arntzen et al. • Frontiers in Robotics and AI (2025)

As aquaculture expands to meet global food demand, it remains dependent on manual, costly, infrequent, and high-risk operations due to reliance on high-end Remotely Operated Vehicles (ROVs). Scalable and autonomous systems are needed to ena...

DOAJ Open Access (DOAJ) DOI: 10.3389/frobt.2025.1655242

Monitoring pedestrian walking dynamics under environmental and policy influences in urban spaces

Mohamed A. Abdelwahab, Shizuo Kaji, Maiya Hori, Shigeru Takano • Computational Urban Science (2026)

Abstract Understanding how environmental conditions and policy interventions jointly shape pedestrian mobility is essential for designing resilient, adaptive, and human-centered urban spaces. This study presents a computer-vision framework ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43762-026-00284-3

Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring

Billie F. Spencer, Vedhus Hoskere, Yasutaka Narazaki • Engineering (2019)

Computer vision techniques, in conjunction with acquisition through remote cameras and unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure condition assessment. The ultimate goal of such a system i...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.eng.2018.11.030

Artificial Intelligence in Healthcare: Advancing Innovation and Ethics to Foster Well-Being

Bayram B., Leventi N., Vodenicharova A., Lamprianidou A. et al. • Acta Medica Bulgarica (2026)

Artificial intelligence (AI) is reshaping healthcare by enhancing diagnostic precision, treatment personalization, and overall patient care. By leveraging technologies such as machine learning, deep learning, natural language processing, an...

DOAJ Open Access (DOAJ) DOI: 10.2478/amb-2026-0050

Resting Posture Recognition Method for Suckling Piglets Based on Piglet Posture Recognition (PPR)–You Only Look Once

Jinxin Chen, Luo Liu, Peng Li, Wen Yao et al. • Agriculture (2025)

The resting postures of piglets are crucial indicators for assessing their health status and environmental comfort. This study proposes a resting posture recognition method for piglets during lactation based on the PPR-YOLO model, aiming to...

DOAJ Open Access (DOAJ) DOI: 10.3390/agriculture15030230