Aydın Ulaş

400 citations
18 papers · 250 · h-index 9

Impact in

Papers in

Aydın Ulaş

18 papers receiving 246 citations

Peers

Aydın Ulaş
Comparison fields: 5 of 55
  • Computer Vision and Pattern Recognition 95
  • Artificial Intelligence 111
  • Computer Networks and Communications 66
  • Signal Processing 21
  • Computational Mathematics 1
Replace Mohammed Falah Mohammed with:
Mohammed Falah Mohammed Malaysia
Shuhua Deng China
Chandan Gautam India
J. Austin United Kingdom
Utpal Nandi India
Xiuxia Tian China
Keiichi Iwamura Japan
Ulrich Finkler United States
Cong Liu China
Aydın Ulaş relative to Mohammed Falah Mohammed Malaysia Mohammed Falah Mohammed's profile →
Citations per field
00.5×1.5×2.4×
Mohammed Falah Mohammed · 1×
Citations per year

Countries citing papers authored by Aydın Ulaş

Since Specialization
Citations

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

Fields of papers citing papers by Aydın Ulaş

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Aydın Ulaş, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Aydın Ulaş Line = papers co-authored together Aydın Ulaş links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 200852
2 200952
3 201136
4 201718
5 201617
6 201116
7 201614
8 201612
9 20118
10 20107
11 20124
12 20124
13
A Multiple Kernel Learning Approach to Multi-Modal Pedestrian Classification
20142
14 20092
15 20152
16 20192
17 20151
18
Selecting Scales by Multiple Kernel Learning for Shape Diffusion Analysis
20111

About Aydın Ulaş

Aydın Ulaş is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Electrical and Electronic Engineering, having authored 18 papers that have together received 250 indexed citations. Recurring topics across this work include Software-Defined Networks and 5G (6 papers), Advanced Neuroimaging Techniques and Applications (4 papers), Face and Expression Recognition (4 papers), Caching and Content Delivery (2 papers), Advanced Statistical Methods and Models (2 papers), Image Retrieval and Classification Techniques (2 papers), Imbalanced Data Classification Techniques (2 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (95 citations), Artificial Intelligence (111 citations), Computer Networks and Communications (66 citations), Signal Processing (21 citations) and Computational Mathematics (1 citation). Aydın Ulaş has collaborated with scholars based in Türkiye, Italy and Netherlands. Frequent co-authors include Olcay Taner Yıldız, Ethem Alpaydın, Bülent Sankur, Lale Akarun, Helin Dutağacı, Berk Gökberk, Burak Görkemli, Didem Gözüpek, Berna Özbek and Vittorio Murino. Their work appears in journals such as Information Sciences, International Journal of Imaging Systems and Technology, Computer Networks, Pattern Recognition and Neurocomputing.

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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