Ümit Budak

35 papers and 1.2k indexed citations i.

About

Ümit Budak is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Ümit Budak has authored 35 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 16 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Artificial Intelligence. Recurrent topics in Ümit Budak’s work include Retinal Imaging and Analysis (10 papers), Digital Imaging for Blood Diseases (8 papers) and AI in cancer detection (7 papers). Ümit Budak is often cited by papers focused on Retinal Imaging and Analysis (10 papers), Digital Imaging for Blood Diseases (8 papers) and AI in cancer detection (7 papers). Ümit Budak collaborates with scholars based in Türkiye, United States and India. Ümit Budak's co-authors include Abdülkadir Şengür, Yanhui Guo, Zafer Cömert, Deniz Korkmaz, Hakan Açıkgöz, Musa Çıbuk, Varun Bajaj, Ceyhun Yıldız, Yaman Akbulut and Erkan Deniz and has published in prestigious journals such as Energy Conversion and Management, Energy and Expert Systems with Applications.

In The Last Decade

Co-authorship network of co-authors of Ümit Budak i

Fields of papers citing papers by Ümit Budak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ümit Budak. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ümit Budak. The network helps show where Ümit Budak may publish in the future.

Countries citing papers authored by Ümit Budak

Since Specialization
Citations

This map shows the geographic impact of Ümit Budak's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ümit Budak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ümit Budak more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

Explore authors with similar magnitude of impact

Rankless by CCL
2025