Ümit Atila

1.3k citations
30 papers · 915 indexed · 1 hit paper · h-index 10
Topics
Digital Imaging for Blood Diseases (5 papers)Speech and Audio Processing (4 papers)AI in cancer detection (4 papers)
Partner nations
TürkiyeMalaysiaLibya

In The Last Decade

Ümit Atila

25 papers receiving 872 citations

Hit Papers

Plant leaf disease classification using EfficientNet deep...20202026202220242020200400600

Peers

Ümit Atila
Comparison fields: 5 of 119
  • Plant Science 498
  • Analytical Chemistry 189
  • Computer Vision and Pattern Recognition 182
  • Artificial Intelligence 154
  • Radiology, Nuclear Medicine and Imaging 92
Replace Kemal Adem with:
Kemal Adem Türkiye
Kemal Akyol Türkiye
Atul Bansal India
Aydın Kaya Türkiye
Arnab Kumar Maji India
Kashif Javed Pakistan
Suneet Gupta India
Ajay Kaul India
Muammer Türkoğlu Türkiye
Shagun Sharma India
Ümit Atila relative to Kemal Adem Türkiye Kemal Adem's profile →
Citations per field
00.5×
Kemal Adem · 1×
Citations per year

Countries citing papers authored by Ümit Atila

Since Specialization
Citations

This map shows the geographic impact of Ümit Atila'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 Atila with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ümit Atila more than expected).

Fields of papers citing papers by Ümit Atila

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ümit Atila. 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 Atila. The network helps show where Ümit Atila may publish in the future.

Co-authorship network of co-authors of Ümit Atila

This figure shows the co-authorship network connecting the top 25 collaborators of Ümit Atila. A scholar is included among the top collaborators of Ümit Atila based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ümit Atila. Ümit Atila is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 2
4 2
5 5
6 0
7 1
8 3
9 0
10 18
11 6
12 13
13 96
14 1
15
Plant leaf disease classification using EfficientNet deep learning modelbreakdown →
602
16 15
17
A Study on Performance Improvement of Heart Disease Prediction by Attribute Selection Methods
4
18 31
19
Design of a route guidance system with shortest driving time based on genetic algorithm
3
20 6

About Ümit Atila

Ümit Atila is a scholar working on Signal Processing, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition, having authored 30 papers that have together received 915 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (5 papers), Speech and Audio Processing (4 papers) and AI in cancer detection (4 papers). The work is most often cited by research in Analytical Chemistry (189 citations), Plant Science (498 citations) and Computer Vision and Pattern Recognition (182 citations). Ümit Atila has collaborated with scholars based in Türkiye, Malaysia and Libya. Frequent co-authors include Kemal Akyol, Emine Uçar, Murat Uçar, İsmail Rakıp Karaş, Fionn Murtagh, Radwan Abu‐Issa, İsmail Şahin, Rafet Durgut, Abdullah Elen and Alias Abdul-Rahman. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Computer Methods and Programs in Biomedicine.

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.

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