Uğur Halıcı
- Cognitive Neuroscience top 2%
- Computer Vision and Pattern Recognition top 5%
- Cellular and Molecular Neuroscience top 5%
- Signal Processing top 2%
- Artificial Intelligence top 5%
- Co-authors
- Yousef R. TabarKemal Leblebi̇ci̇oğluMehmet Sinan BeksaçVolkan AtalayÜmit BudakAbdulkadir ŞengürMeral BeksaçŞeyda Ertekin
- Topics
- Automated Road and Building Extraction (11 papers)Neural Networks and Applications (10 papers)Remote Sensing and LiDAR Applications (8 papers)
- Journals
- Proceedings of the IEEEEuropean Journal of Operational ResearchIndustrial & Engineering Chemistry Research
- Partner nations
- TürkiyeCyprusUnited States
In The Last Decade
Uğur Halıcı
65 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Cognitive Neuroscience 672
- Computer Vision and Pattern Recognition 354
- Cellular and Molecular Neuroscience 289
- Signal Processing 269
- Artificial Intelligence 250
Countries citing papers authored by Uğur Halıcı
This map shows the geographic impact of Uğur Halıcı'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 Uğur Halıcı with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Uğur Halıcı more than expected).
Fields of papers citing papers by Uğur Halıcı
This network shows the impact of papers produced by Uğur Halıcı. 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 Uğur Halıcı. The network helps show where Uğur Halıcı may publish in the future.
Co-authorship network of co-authors of Uğur Halıcı
This figure shows the co-authorship network connecting the top 25 collaborators of Uğur Halıcı. A scholar is included among the top collaborators of Uğur Halıcı 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 Uğur Halıcı. Uğur Halıcı is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 0 | |
| 3 | A novel deep learning approach for classification of EEG motor imagery signalsbreakdown → | 659 |
| 4 | 9 | |
| 5 | 8 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 4 | |
| 12 | Training Radial Basis Function Neural Networks through Parabolic Evolutionary Algorithm. | 2 |
| 13 | 20 | |
| 14 | 3 | |
| 15 | Correctness of Workflow in the Presence of Concurrency. | 3 |
| 16 | 9 | |
| 17 | 5 | |
| 18 | 62 | |
| 19 | 1 | |
| 20 | 4 |
About Uğur Halıcı
Uğur Halıcı is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 69 papers that have together received 1.4k indexed citations. Recurring topics across this work include Automated Road and Building Extraction (11 papers), Neural Networks and Applications (10 papers) and Remote Sensing and LiDAR Applications (8 papers). The work is most often cited by research in Cognitive Neuroscience (672 citations), Signal Processing (269 citations) and Human-Computer Interaction (134 citations). Uğur Halıcı has collaborated with scholars based in Türkiye, Cyprus and United States. Frequent co-authors include Yousef R. Tabar, Kemal Leblebi̇ci̇oğlu, Mehmet Sinan Beksaç, Volkan Atalay, Ümit Budak, Abdulkadir Şengür, Meral Beksaç, Şeyda Ertekin, Asuman Doğaç and Murat Karabatak. Their work appears in journals such as Proceedings of the IEEE, European Journal of Operational Research and Industrial & Engineering Chemistry Research.
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.