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Uğur Şevik

ResearcherPublications, citations & collaboration network

Uğur Şevik is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 15 works, 431 citations, an h-index of 6 and an i10-index of 6.

15
Works
431
Citations
6
h-index
6
i10-index

How has Uğur Şevik's publication output changed over time?

ScholarIQpublication output · 2007–2025

Output grew200% over the shown period — from 1 works in 2007 to 3 in 2025.

1
2
1
1
1
1
3
2007200820112014201720192025

What are the most-cited papers on Uğur Şevik?

ScholarIQmost cited works
Identification of suitable fundus images using automated quality assessment methods
Uğur Şevik, Cemal Köse, Tolga Berber, Hidayet Erdöl
S117354312. 2014112 CitationsOPEN ACCESS
Simple methods for segmentation and measurement of diabetic retinopathy lesions in retinal fundus images
Cemal Köse, Uğur Şevik, Cevat İkibaş, Hidayet Erdöl
Computer Methods and Programs in Biomedicine. 201189 Citations
Automatic segmentation of age-related macular degeneration in retinal fundus images
Cemal Köse, Uğur Şevik, Okyay Gençalioğlu
S44278595. 200874 Citations
A Statistical Segmentation Method for Measuring Age-Related Macular Degeneration in Retinal Fundus Images
Cemal Köse, Uğur Şevik, Okyay Gençalioğlu, Cevat İkibaş, Temel Kayıkıçıoğlu
Journal of Medical Systems. 200863 Citations
Automatic classification of skin burn colour images using texture‐based feature extraction
Uğur Şevik, Erdinç Karakullukçu, Tolga Berber, Yeşim Akbaş, Serdar Türkyılmaz
S83215360. 201944 Citations

Related on ScholarIQ

Karadeniz Technical University
Institution
Identification of suitable fundus images using automated quality assessment methods
Paper
Simple methods for segmentation and measurement of diabetic retinopathy lesions in retinal fundus images
Paper
Automatic segmentation of age-related macular degeneration in retinal fundus images
Paper
A Statistical Segmentation Method for Measuring Age-Related Macular Degeneration in Retinal Fundus Images
Paper
Automatic classification of skin burn colour images using texture‐based feature extraction
Paper
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