Değer Ayata

634 citations
11 papers · 439 indexed · h-index 8

Değer Ayata

10 papers receiving 421 citations

Peers

Değer Ayata
Comparison fields: 5 of 67
  • Experimental and Cognitive Psychology 212
  • Cognitive Neuroscience 178
  • Signal Processing 79
  • Human-Computer Interaction 25
  • Computer Vision and Pattern Recognition 86
Replace Divyashikha Sethia with:
Divyashikha Sethia India
Norhaslinda Kamaruddin Malaysia
Wei Tao China
Samarth Tripathi India
Zhongtian Bao China
Joep J. M. Kierkels Switzerland
Juan Carlos Martínez-Santos Colombia
Mohan Karnati India
A. M. Mutawa Kuwait
Suja Palaniswamy India
Değer Ayata relative to Divyashikha Sethia India Divyashikha Sethia's profile →
Citations per field
00.5×1.5×2.5×
Divyashikha Sethia · 1×
Citations per year

Countries citing papers authored by Değer Ayata

Since Specialization
Citations

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

Fields of papers citing papers by Değer Ayata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 4 scholars most cited alongside Değer Ayata, 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 Değer Ayata Line = papers co-authored together Değer Ayata links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 20240
2 20241
3 2020120
4 2018177
5 20183
6 201711
7 201713
8 201726
9
Emotion Recognition via Galvanic Skin Response: Comparison of Machine Learning Algorithms and Feature Extraction Methods
201742
10 20178
11 201638

About Değer Ayata

Değer Ayata is a scholar working on Experimental and Cognitive Psychology, Cognitive Neuroscience, Artificial Intelligence, Marketing and Social Psychology, having authored 11 papers that have together received 439 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (5 papers), EEG and Brain-Computer Interfaces (3 papers), Sentiment Analysis and Opinion Mining (3 papers), Topic Modeling (2 papers), Advanced Text Analysis Techniques (2 papers), Color perception and design (2 papers), Neural dynamics and brain function (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (212 citations), Cognitive Neuroscience (178 citations), Signal Processing (79 citations), Human-Computer Interaction (25 citations) and Computer Vision and Pattern Recognition (86 citations). Değer Ayata has collaborated with scholars based in Türkiye. Frequent co-authors include Yusuf Yaslan, Mustafa E. Kamaşak, Arzucan Özgür and Murat Saraçlar. Their work appears in journals such as IEEE Transactions on Consumer Electronics, Journal of Medical and Biological Engineering, DergiPark (Istanbul University) and Istanbul Technical University Academic Open Archive (Istanbul Technical University).

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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