Nafiz Arıca
- Computer Vision and Pattern Recognition top 1%
- Media Technology top 1%
- Artificial Intelligence top 10%
- Cognitive Neuroscience
- Aerospace Engineering
- Co-authors
- Fatoş T. Yarman-VuralFatoş T. Yarman VuralKadir Alpaslan DemirOğuz TanSerap AydınNarendra AhujaSoheil SalahshourMd Baharul Islam
- Topics
- Image Retrieval and Classification Techniques (13 papers)Face recognition and analysis (10 papers)Advanced Image and Video Retrieval Techniques (10 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Neural Networks and Learning SystemsPattern Recognition Letters
- Partner nations
- TürkiyeCanadaUnited States
In The Last Decade
Nafiz Arıca
50 papers receiving 809 citations
Peers
Comparison fields: 5 of 112
- Computer Vision and Pattern Recognition 718
- Media Technology 288
- Artificial Intelligence 188
- Cognitive Neuroscience 60
- Aerospace Engineering 48
Countries citing papers authored by Nafiz Arıca
This map shows the geographic impact of Nafiz Arıca'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 Nafiz Arıca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nafiz Arıca more than expected).
Fields of papers citing papers by Nafiz Arıca
This network shows the impact of papers produced by Nafiz Arıca. 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 Nafiz Arıca. The network helps show where Nafiz Arıca may publish in the future.
Co-authorship network of co-authors of Nafiz Arıca
This figure shows the co-authorship network connecting the top 25 collaborators of Nafiz Arıca. A scholar is included among the top collaborators of Nafiz Arıca 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 Nafiz Arıca. Nafiz Arıca is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 15 | |
| 8 | Underwater Acoustic Signal Recognition Methods | 3 |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 12 | |
| 12 | Scene Classification Using Cascaded Probabilistic Latent Semantic Analysis | 1 |
| 13 | 2 | |
| 14 | 13 | |
| 15 | 122 | |
| 16 | 4 | |
| 17 | 22 | |
| 18 | 335 | |
| 19 | 11 | |
| 20 | A new HMM topology for shape recognition. | 2 |
About Nafiz Arıca
Nafiz Arıca is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Media Technology, having authored 55 papers that have together received 939 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (13 papers), Face recognition and analysis (10 papers) and Advanced Image and Video Retrieval Techniques (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (718 citations), Media Technology (288 citations) and Human-Computer Interaction (47 citations). Nafiz Arıca has collaborated with scholars based in Türkiye, Canada and United States. Frequent co-authors include Fatoş T. Yarman-Vural, Fatoş T. Yarman Vural, Kadir Alpaslan Demir, Oğuz Tan, Serap Aydın, Narendra Ahuja, Soheil Salahshour, Md Baharul Islam, Sarp Ertürk and Adnan Yazıcı. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems and Pattern Recognition Letters.
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.