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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

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

Image fusion method based on simultaneous sparse representation with non‐subsampled contourlet transform

Guiqing He, Siyuan Xing, Xingjian He, Jun Wang et al. • IET Computer Vision (2019)

The image fusion method based on sparse representation in the single‐scale image domain has produced better fusion results than the classic methods based on multi‐scale analysis nowadays. However, due to the limited number of dictionary ato...

DOAJ Open Access (DOAJ) DOI: 10.1049/iet-cvi.2018.5496

Sparse Representation for Computer Vision and Pattern Recognition

John N. Wright, Yi Ma, Julien Mairal, Guillermo Sapiro et al. • Proceedings of the IEEE (2010)

Techniques from sparse signal representation are beginning to see significant impact in computer vision, often on nontraditional applications where the goal is not just to obtain a compact high-fidelity representation of the observed signal...

OPENALEX DOI: https://doi.org/10.1109/jproc.2010.2044470

A Taxonomy of Deep Convolutional Neural Nets for Computer Vision

Suraj Srinivas, Ravi Kiran Sarvadevabhatla, Konda Reddy Mopuri, Nikita Prabhu et al. • Frontiers in Robotics and AI (2016)

Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features. However, of late, deep learning techniques have offered a compelling alternative -- th...

OPENALEX cc-by DOI: https://doi.org/10.3389/frobt.2015.00036

Deep Learning for Understanding Satellite Imagery: An Experimental Survey

Sharada Prasanna Mohanty, Jakub Czakon, Kamil A. Kaczmarek, Kamil A. Kaczmarek et al. • Frontiers in Artificial Intelligence (2020)

Translating satellite imagery into maps requires intensive effort and time, especially leading to inaccurate maps of the affected regions during disaster and conflict. The combination of availability of recent datasets and advances in compu...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2020.534696

Toward Automated Structural Design for Controlled Vibration Characteristics Using Topology Optimization and Computer Vision in Space Missions

Musaddiq Al Ali, Masatoshi Shimoda, Marc Naguib • Applied Sciences (2024)

This study explores the integration of computer vision with topology optimization for additive manufacturing, with a focus on maximizing eigenfrequency in a design domain. Utilizing custom-developed photogrammetry software, high-resolution ...

DOAJ Open Access (DOAJ) DOI: 10.3390/app14156786

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera et al. • IEEE Access (2020)

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to autonomous driving of modern cars as well as other sectors in ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3039858

GUI testing using computer vision

Tsung-Hsiang Chang, TOM P. YEH, Robert C. Miller • CHI Conference on Human Factors in Computing Systems (2010)

Testing a GUI's visual behavior typically requires human testers to interact with the GUI and to observe whether the expected results of interaction are presented. This paper presents a new approach to GUI testing using computer vision for ...

OPENALEX Open Access DOI: https://doi.org/10.1145/1753326.1753555

Visual servoing for robot control: Learning activities using RoboDKde robots: actividades de aprendizaje con RoboDK

Raidell Avello-Martínez, Abraham Prieto García • Edutec (2025)

Visual servo control is a key robotic control technique that uses visual feedback to dynamically adjust movements. This study, conducted within the AIM@VET project, evaluates the effectiveness of a RoboDK-based lesson with 25 vocational stu...

DOAJ Open Access (DOAJ) DOI: 10.21556/edutec.2025.94.3955

Impact of Water Depth on Subway Emergency Evacuation in Flood Scenarios

ZHU Wenhao, ZHU Haiyan, LIU Zhigang, SHEN Yuxin et al. • Chengshi guidao jiaotong yanjiu (2025)

[Objective] Evacuation bottlenecks for subway stations in flood scenarios are investigated to enhance subway station personnel evacuation efficiency under water inundation and backflow conditions, and provide insights for developing subway ...

DOAJ Open Access (DOAJ) DOI: 10.16037/j.1007-869x.20231053

Up-to-Date Scoping Review of Object Detection Methods for Macro Marine Debris

Zoe Moorton, Kamlesh Mistry, Rebecca Strachan, Shanfeng Hu • Journal of Marine Science and Engineering (2025)

Being able to accurately identify litter in a marine environment is crucial to cleaning up our seas and oceans. Research into object detection techniques to support this identification has been underway for over two decades. However, there ...

DOAJ Open Access (DOAJ) DOI: 10.3390/jmse13081590

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

From Data to Decisions: AI in Varicose Veins—Predicting, Diagnosing, and Guiding Effective Management

Lakshmi Sree Pugalenthi, Chris Garapati, Srivarshini Maddukuri, Fnu Kanwal et al. • Journal of Vascular Diseases (2025)

Background: Varicose veins (VVs) of the lower limbs, characterized by palpable, dilated, and tortuous veins, affect 2–73% of the global population. Artificial intelligence (AI) offers significant potential to enhance healthcare efficiency a...

DOAJ Open Access (DOAJ) DOI: 10.3390/jvd4020019

HawkEye: AI-Driven Software for Objective Analysis and Characterization of Nodular Cast Iron Microstructures

Javier Nieves, Antonio Serena-Barriuso, Guillermo Elejoste-Rementeria • Applied Sciences (2025)

Metallographic evaluation of nodular cast iron is crucial for quality control in the foundry industry. Traditionally, this process relies on experts who visually interpret microscopic images. This study introduces HawkEye, a comprehensive s...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15136991