Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object A Comparative Study of Attention-Augmented YOLO Architectures for Defect Detection in Fused Deposition Modelling(Institute of Electrical and Electronics Engineers Inc., 2025) Cezayirli, H.; Tetik, H.; Dede, M.I.C.; Phone, W.L.; Alkan, B.Additive manufacturing (AM), particularly fused deposition modelling (FDM), facilitates the fabrication of complex geometries with increasing flexibility and efficiency. Ensuring consistent print quality in FDM processes necessitates the development of accurate defect detection mechanisms. Attention-augmented YOLO (You Only Look Once) models have emerged as a promising solution for addressing this challenge. In this study, we systematically benchmark and evaluate the performance of YOLO architectures enhanced with attention mechanisms within the context of FDM 3D printing applications. The models were trained and evaluated using representative defect datasets. The attention-augmented models demonstrate improved detection performance. © 2025 IEEE.Book Part Citation - Scopus: 1Online Urban Information Systems(IGI Global, 2008) Yigitcanlar, Tan; Saygin, ÖmürCountless factors affect the inner workings of a city, so in an attempt to gain an understanding of place and making sound decisions, planners need to utilize decision support systems (DSS) or planning support systems (PSS). PSS were originally developed as DSS in academia for experimental purposes, but like many other technologies, they became one of the most innovative technologies in parallel to rapid developments in software engineering as well as developments and advances in networks and hardware. Particularly, in the last decade, the awareness of PSS have been dramatically heightened with the increasing demand for a better, more reliable and furthermore a transparent decision-making process (Klosterman, Siebert, Hoque, Kim, & Parveen, 2003). Urban planning as an act has quite different perspective from the PSS point of view. The unique nature of planning requires that spatial dimension must be considered within the context of PSS. Additionally, the rapid changes in socio-economic structure cannot be easily monitored or controlled without an effective PSS. © 2025 Elsevier B.V., All rights reserved.Article Citation - Scopus: 3University Librarians’ Perceptions of Artificial Intelligence, Its Application Areas in Libraries, and The Future(University and Research Librarians Association (UNAK), 2024) Gürdal, Gültekin; Çuhadar, Sami; Mert, Selma; Gezer, Çağatay; Helvacıoğlu, Ece; Arus, Oya; Aslan, Özlem; Karslı, Melahat; Sönmez, Çiğdem; Taş, Ali; Açıkalın, Cansu; Mazlumoğlu, Ayça Aydemir; Erken, Mehmet; Yılmaz, Müberra; Çerkez, Özlem Araz; Uğur, Emrullah; Menemenlioğlu, Alper; Şenoğlu, Aysel; Atlı, Songül; Cuhadar, Sami; Gurdal, Gultekin; Erken, Mehmet; Mert, Selma; Gezer, Cagatay; Helvacıoğlu, Ece; Atli, SongülGünümüzde kütüphaneler, değişen teknoloji ve yeniliklerden etkilenen kurumlar arasında yer almaktadır. Yapay zeka teknolojilerinin popüler hale gelmesi, kütüphane hizmetlerini de dönüştürmeye başlamıştır. Bu araştırmada, Türkiye’deki üniversite kütüphanelerinin yapay zeka teknoloji ve uygulamalarının gelişim sürecinde yapmış olduğu ve yapmayı planladığı düzenlemeleri tespit etmek ve ilgili döneme özel geliştirdikleri hizmetleri belirlemek amacıyla bir anket uygulanmıştır. Anket, Türkiye’deki 208 üniversite kütüphanesinden 111 üniversite kütüphanesi yöneticisinin katılımıyla gerçekleştirilmiştir. Verilerin analizi ile üniversite kütüphanelerinin yapay zeka teknolojileri ve uygulamaları hakkındaki durumu, bilgi ve farkındalık düzeyleri belirlenmiş, eksik ve zayıf yönlerin geliştirilmesine yönelik önlemler ve öneriler sunulmuştur. İlgili araştırma, yapay zeka konusunda Türkiye’de üniversite kütüphanesi yöneticilerinden görüş ve öneri alarak gerçekleştirilen ilk ve en kapsamlı çalışmadır. Araştırma bulguları, üniversite kütüphanelerinin ChatGPT, Gemini, Grammarly vb. yapay zeka uygulamalarını belirli düzeyde kullandıklarını ancak yapay zeka ile ilgili kurumsal politika geliştirme, personele yetkinlik kazandırma ve planlama konularında ihtiyaçlarının olduğu ortaya çıkmıştır.Article Citation - Scopus: 20Estrus Detection and Dairy Cow Identification With Cascade Deep Learning for Augmented Reality-Ready Livestock Farming(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Arıkan, İ.; Ayav, T.; Seçkin, A.Ç.; Soygazi, F.Accurate prediction of the estrus period is crucial for optimizing insemination efficiency and reducing costs in animal husbandry, a vital sector for global food production. Precise estrus period determination is essential to avoid economic losses, such as milk production reductions, delayed calf births, and disqualification from government support. The proposed method integrates estrus period detection with cow identification using augmented reality (AR). It initiates deep learning-based mounting detection, followed by identifying the mounting region of interest (ROI) using YOLOv5. The ROI is then cropped with padding, and cow ID detection is executed using YOLOv5 on the cropped ROI. The system subsequently records the identified cow IDs. The proposed system accurately detects mounting behavior with 99% accuracy, identifies the ROI where mounting occurs with 98% accuracy, and detects the mounting couple with 94% accuracy. The high success of all operations with the proposed system demonstrates its potential contribution to AR and artificial intelligence applications in livestock farming. © 2023 by the authors.