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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

Computer Vision Meets Educational Robotics

Aphrodite Sophokleous, Panayiotis Christodoulou, Lefteris Doitsidis, Savvas A. Chatzichristofis • Electronics (2021)

Educational robotics has gained a lot of attention in the past few years in K-12 education. Prior studies have shown enough shreds of evidence and highlight the benefits of educational robotics as being effective in providing impactful lear...

OPENALEX cc-by DOI: https://doi.org/10.3390/electronics10060730

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

Experimental study of a novel contact-based pose detection approach for digital twin-driven high-precision micro assembly

Nazeer Bilal, Pradeep Carol Santhosh, Vargas Patricia A., Erden Mustafa Suphi et al. • Manufacturing Review (2025)

This study presents a comprehensive study of a novel Contact-Based Pose Estimation Method (CBPEM) for enhancing precision in robotic assembly processes within digital twin frameworks. Conventional pose detection methods, such as laser and c...

DOAJ Open Access (DOAJ) DOI: 10.1051/mfreview/2025004

A lightweight optimization framework for real-time pedestrian detection in dense and occluded scenes

C. Chen, J. Li, J. Li, Z. Shuai et al. • Mechanical Sciences (2025)

Pedestrian detection is one of the most widely applied tasks in industrial computer vision. It encapsulates three core challenges of object detection: detecting small objects, handling heavy occlusion, and balancing speed and accuracy for d...

DOAJ Open Access (DOAJ) DOI: 10.5194/ms-16-877-2025

A Wilson–Cowan reservoir computer for interpretable spatiotemporal vision

Sharmarke A. Gabayre, Sergey Savel’ev, Varuna De Silva, Mindula Illeperuma et al. • Scientific Reports (2026)

Abstract We present a Wilson–Cowan reservoir computer (WC–RC) that treats a retinotopic excitatory–inhibitory neural field as a structured reservoir. Travelling waves and bounded oscillations provide an interpretable spatiotemporal basis, w...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-49359-5

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

Spatially Aware Fusion in 3D Convolutional Autoencoders for Video Anomaly Detection

Asim Niaz, Sareer Ul Amin, Shafiullah Soomro, Hamza Zia et al. • IEEE Access (2024)

Surveillance videos are crucial for crime prevention and public safety, yet the challenge of defining abnormal events hinders their effectiveness, limiting the applicability of supervised methods. This paper introduces an unsupervised end-t...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3435144

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

A Survey of Deep Learning Techniques and Computer Vision in Robotic and Drone with Applications

Khazaal Abbas Maaroof Maysoon, Bouhlel Med Salim • BIO Web of Conferences (2024)

The methods of deep learning have lately demonstrated outstanding outcomes of robotic objects such as imagination, localization and striping. Its exceptional abilities in order to learn idealizations from complicated data gathered in the re...

DOAJ Open Access (DOAJ) DOI: 10.1051/bioconf/20249700008

Spatiotemporal patterns induced by four mechanisms in a tussock sedge model with discrete time and space variables

You Li, Jingjing Cao, Ying Sun, Dan Song et al. • Advances in Difference Equations (2021)

Abstract In this paper, we investigate the spatiotemporal patterns of a freshwater tussock sedge model with discrete time and space variables. We first analyze the kinetic system and show the parametric conditions for flip and Neimark–Sacke...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13662-021-03557-9

Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems

Dimitra G. Georgopoulou, Orestis Stavrakidis-Zachou, Orestis Stavrakidis-Zachou, Nikos Mitrizakis et al. • Frontiers in Animal Science (2021)

Monitoring and understanding fish behavior is crucial for achieving precision in everyday husbandry practices (i.e. for optimizing farm performance), and for improving fish welfare in aquaculture. Various intelligent monitoring and control ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fanim.2021.754520