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Very large‐scale integration architecture for video stabilisation and implementation on a field programmable gate array‐based autonomous vehicle

Tahiyah Nou‐Shene, Vikramkumar Pudi, K. Sridharan, Vineetha Thomas et al. • IET Computer Vision (2015)

Autonomous vehicles engaged in terrain exploration are typically equipped with a camera. The camera is subjected to vibration as the vehicle moves so that the videos captured require stabilisation to facilitate accurate interpretation by re...

DOAJ Open Access (DOAJ) DOI: 10.1049/iet-cvi.2014.0120

Artificial Intelligence in Routine IVF Practice

Grzegorz Mrugacz, Aleksandra Mospinek, Małgorzata Jagielska, Dariusz Miszczak et al. • Biology (2025)

Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...

DOAJ Open Access (DOAJ) DOI: 10.3390/biology15010042

Bridging the performance–efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection

Rittik Chandra Das Turjy, Fahmid Al Farid, Fahmid Al Farid, Md. Hasan Imam Bijoy et al. • Frontiers in Artificial Intelligence (2026)

Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1884567

Kernel Methods in Computer Vision

Christoph H. Lampert • Foundations and Trends® in Computer Graphics and Vision (2009)

Over the last years, kernel methods have established themselves as powerful tools for computer vision researchers as well as for practitioners. In this tutorial, we give an introduction to kernel methods in computer vision from a geometric ...

OPENALEX DOI: https://doi.org/10.1561/0600000027

Deep learning based computer vision approaches for smart agricultural applications

V. G. Dhanya, Anakkallan Subeesh, Nand Lal Kushwaha, Dinesh Kumar Vishwakarma et al. • Artificial Intelligence in Agriculture (2022)

The agriculture industry is undergoing a rapid digital transformation and is growing powerful by the pillars of cutting-edge approaches like artificial intelligence and allied technologies. At the core of artificial intelligence, deep learn...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.aiia.2022.09.007

A Systematic YOLO-Specific Model Selection for Mechanical Fault Identification in High-Voltage Insulators

Arailym Serikbay, Venera Nurmanova, Yerbol Akhmetov, Amin Zollanvari et al. • International Transactions on Electrical Energy Systems (2025)

Regular monitoring of outdoor insulators is crucial to ensure the reliable functioning of the power grid. With recent progress in computer vision technologies, traditional manual and expensive visual inspections can now be replaced by autom...

DOAJ Open Access (DOAJ) DOI: 10.1155/etep/8669289

VISION-LINK AI Smart Glass: An Edge-Cloud Wearable AI System for Workflow Automation and Digital Inclusion in Emerging Economies

Buhari Salisu • International Journal of AI and Advanced Computing (2026)

The rapid advancement of Artificial Intelligence (AI), wearable computing, and Internet of Things (IoT) technologies has significantly transformed digital interactions across various sectors. However, the adoption of smart wearable technolo...

DOAJ Open Access (DOAJ) DOI: 10.5281/zenodo.21981139

Assessing Wireless Sensing Potential With Large Intelligent Surfaces

Cristian J. Vaca-Rubio, Pablo Ramirez-Espinosa, Kimmo Kansanen, Zheng-Hua Tan et al. • IEEE Open Journal of the Communications Society (2021)

Sensing capability is one of the most highlighted new feature of future 6G wireless networks. This paper addresses the sensing potential of Large Intelligent Surfaces (LIS) in an exemplary Industry 4.0 scenario. Besides the attention receiv...

DOAJ Open Access (DOAJ) DOI: 10.1109/OJCOMS.2021.3073467

An accurate, efficient, and accessible AI-powered solution for wildlife re-identification in conservation

Shahrzad Gholami, Derek E. Lee, Caleb Robinson, Monica L. Bond et al. • Scientific Reports (2026)

Abstract Accurate wildlife re-identification is critical for a wide range of ecological studies, including density estimation via capture–recapture, demographic analyses, and behavioral research. We pr esent GIRAFFE (Generalized Image-based...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-54115-w

OpenCV for Computer Vision Applications

Ekta Sinha, Ashwani Kumar, Abhinav Tyagi • International Journal For Multidisciplinary Research (2025)

OpenCV is a powerful, open-source toolkit designed for handling real-time computer vision challenges and advanced image processing tasks. It enables automated systems to interpret images and videos effectively. This paper explores the capab...

OPENALEX cc-by-sa DOI: https://doi.org/10.36948/ijfmr.2025.v07i03.44280

The Validity and Reliability of the My Jump Lab App for the Measurement of Vertical Jump Performance Using Artificial Intelligence

Carlos Balsalobre-Fernández, Daniel Varela-Olalla • Sensors (2024)

The countermovement jump (CMJ) is a widely used test to assess lower body neuromuscular performance. This study aims to analyze the validity and reliability of an iOS application using artificial intelligence to measure CMJ height, force, v...

DOAJ Open Access (DOAJ) DOI: 10.3390/s24247897

An Implementation of an optimized dual-axis solar tracking algorithm for concentrating solar power plants deployment

Eric Tutu Tchao, Simon Atuah Asakipaam, Yesuenyeagbe Atsu Kwabla Fiagbe, Bright Yeboah-Akowuah et al. • Scientific African (2022)

A recent assessment of a pilot concentrating solar power plant in Ghana noticed the failure of the tracking system to accurately align the multifaceted heliostats toward the sun and focus the sunbeams onto the target. A further review of so...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.sciaf.2022.e01228

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