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Automated Burr Quality Classification in Drilling of AA6013 Aluminum Alloy Using YOLOv10n

Mikail Kırğıl, Suleyman Gokhan Taskin, Ali Ercetin • Applied Sciences (2026)

Burr formation during drilling of aluminum alloys can compromise hole quality and assembly accuracy, increasing the need for secondary deburring operations. The time-consuming and operator-dependent nature of manual visual inspection create...

DOAJ Open Access (DOAJ) DOI: 10.3390/app162010012

Estimating Black Oat Biomass Using Digital Surface Models and a Vegetation Index Derived from RGB-Based Aerial Images

Lucas Renato Trevisan, Lisiane Brichi, Tamara Maria Gomes, Fabrício Rossi • Remote Sensing (2023)

Responsible for food production and industry inputs, agriculture needs to adapt to worldwide increasing demands and environmental requirements. In this scenario, black oat has gained environmental and economic importance since it can be use...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs15051363

Fundamentals of Computer Vision

Wesley E. Snyder, Hairong Qi • Cambridge University Press eBooks (2017)

Computer vision has widespread and growing application including robotics, autonomous vehicles, medical imaging and diagnosis, surveillance, video analysis, and even tracking for sports analysis. This book equips the reader with crucial mat...

OPENALEX DOI: https://doi.org/10.1017/9781316882641

Federated Learning in Computer Vision

Donald Shenaj, Giulia Rizzoli, Pietro Zanuttigh • IEEE Access (2023)

Federated Learning (FL) has recently emerged as a novel machine learning paradigm allowing to preserve privacy and to account for the distributed nature of the learning process in many real-world settings. Computer vision tasks deal with hu...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1109/access.2023.3310400

Advanced Swine Management: Infrared Imaging for Precise Localization of Reproductive Organs in Livestock Monitoring

Iyad Almadani, Brandon Ramos, Mohammed Abuhussein, Aaron L. Robinson • Digital (2024)

Traditional methods for predicting sow reproductive cycles are not only costly but also demand a larger workforce, exposing workers to respiratory toxins, repetitive stress injuries, and chronic pain. This occupational hazard can even lead ...

DOAJ Open Access (DOAJ) DOI: 10.3390/digital4020022

Performance Benchmarking: Pre-trained Models and Custom Convolutional Neural Networks in Deep Learning

Sheemona Joseph C., S. Ganesh, S. Kannadhasan, K. Selvipriya • Journal of Informatics and Web Engineering (2025)

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffic signs—a crucial ta...

DOAJ Open Access (DOAJ) DOI: 10.33093/jiwe.2025.4.2.14