Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Book Part Citation - Scopus: 4Bacteria: Arcobacter(Elsevier, 2014) Atabay, Halil İbrahim; Corry, Janet E.L.; Ceylan, ÇağatayThe genus Arcobacter currently comprises many phenotypically different species isolated from diverse niches. Although some Arcobacter spp. (particularly, Arcobacter butzleri, Arcobacter skirrowii, and Arcobacter cryaerophilus) are associated with various diseases in humans and animals, their exact epidemiological and pathological role is not completely understood, and few cases of human infection are reported. The primary mode of Arcobacter transmission is thought to occur via contaminated water and food and contact with pets. As some species are difficult to cultivate and all are difficult to identify using conventional biochemical tests, nucleic acid-based techniques such as polymerase chain reaction (PCR) and real-time PCR are increasingly used for their simultaneous detection, identification, and quantification. Their tendency to be resistant to antibiotics, and their ability to colonize food processing environments indicate that they could cause serious disease in the human population, particularly in susceptible individuals with impaired immune response. © 2014 Elsevier Inc. All rights reserved.Conference Object Citation - WoS: 2Citation - Scopus: 2Türkçe Manzara Metni Veri Kümesi(IEEE, 2017) Erdogmus, NesliScene text localization and recognition keeps attracting an increasing interest from researchers due to its valuable advantage in extracting content from real world images and in image retrieval via text search. Nevertheless, due to the fact that the majority of the image datasets that are commonly used in this field is comprised of text in English, the related studies have mostly been limited to a single language. On that account, in order to apply the technologies developed for scene text detection and recognition to Turkish scene text, analyze their performances and to develop Turkish language specific algorithms, a Turkish scene text database is collected for the first time in the literature. In this paper, the contents of this database, shortly called STRIT (Scene Text Recognition In Turkish), are detailed. Additionally, two baseline methods are tested to detect and recognize scene text in Turkish and the preliminary results are presented.