Aydın Kaya

899 total citations · 1 hit paper
26 papers, 635 citations indexed

About

Aydın Kaya is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Aydın Kaya has authored 26 papers receiving a total of 635 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Aydın Kaya's work include Anomaly Detection Techniques and Applications (9 papers), Human Pose and Action Recognition (8 papers) and Video Surveillance and Tracking Methods (4 papers). Aydın Kaya is often cited by papers focused on Anomaly Detection Techniques and Applications (9 papers), Human Pose and Action Recognition (8 papers) and Video Surveillance and Tracking Methods (4 papers). Aydın Kaya collaborates with scholars based in Türkiye, Netherlands and United States. Aydın Kaya's co-authors include Ali Seydi Keçeli, Cagatay Catal, Bedir Teki̇nerdoğan, Hamdi Yalın Yalıç, Ahmet Burak Can, Öner Özdoğan, Paulo Costa, Hayri Sever, Thabet Kacem and Ufuk Şener and has published in prestigious journals such as Sensors, Computers and Electronics in Agriculture and Electronics Letters.

In The Last Decade

Aydın Kaya

25 papers receiving 607 citations

Hit Papers

Analysis of transfer learning for deep neural network bas... 2019 2026 2021 2023 2019 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Analysis of transfer learning for deep neural network based plant classification models
    2019 318 citations Aydın Kaya, Ali Seydi Keçeli et al. Computers and Electronics in Agriculture profile →

Peers

Aydın Kaya
Kemal Adem Türkiye
Ümit Atila Türkiye
Murat Uçar Türkiye
Emine Uçar Türkiye
Henrik Karstoft Denmark
Rodrigo Pereira Ramos Brazil
Jinglei Tang China
Anushikha Singh India
Mei Jiang China
Aravind Krishnaswamy Rangarajan India
Kemal Adem Türkiye
Aydın Kaya
Citations per year, relative to Aydın Kaya Aydın Kaya (= 1×) peers Kemal Adem

Countries citing papers authored by Aydın Kaya

Since Specialization
Citations

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

Fields of papers citing papers by Aydın Kaya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aydın Kaya

This figure shows the co-authorship network connecting the top 25 collaborators of Aydın Kaya. A scholar is included among the top collaborators of Aydın Kaya 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 Aydın Kaya. Aydın Kaya 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
1.
Keçeli, Ali Seydi, et al.. (2024). A shallow 3D convolutional neural network for violence detection in videos. Egyptian Informatics Journal. 26. 100455–100455. 5 indexed citations
2.
Keçeli, Ali Seydi & Aydın Kaya. (2022). Violent activity classification with transferred deep features and 3d-Cnn. Signal Image and Video Processing. 17(1). 139–146. 9 indexed citations
3.
Kacem, Thabet, et al.. (2021). ADS-B Attack Classification using Machine Learning Techniques. Qatar University QSpace (Qatar University). 7–12. 3 indexed citations
4.
Keçeli, Ali Seydi, Cagatay Catal, Aydın Kaya, & Bedir Teki̇nerdoğan. (2020). Development of a recurrent neural networks-based calving prediction model using activity and behavioral data. Computers and Electronics in Agriculture. 170. 105285–105285. 45 indexed citations
5.
Kaya, Aydın, et al.. (2019). Analysis of transfer learning for deep neural network based plant classification models. Computers and Electronics in Agriculture. 158. 20–29. 318 indexed citations breakdown →
6.
Kaya, Aydın. (2018). Cascaded classifiers and stacking methods for classification of pulmonary nodule characteristics. Computer Methods and Programs in Biomedicine. 166. 77–89. 27 indexed citations
7.
Keçeli, Ali Seydi & Aydın Kaya. (2018). Optik Akış Görüntüsü ve Bi-Lstm ile Şiddet İçeren Hareketlerin Sınıflandırılması. European Journal of Science and Technology. 204–208. 1 indexed citations
8.
Kaya, Aydın, Ali Seydi Keçeli, & Ahmet Burak Can. (2018). Akciğer nodül özelliklerinin tahmininde çeşitli sınıflama stratejilerinin incelenmesi. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi. 2018(2018). 5 indexed citations
9.
Keçeli, Ali Seydi, Aydın Kaya, & Ahmet Burak Can. (2018). Combining 2D and 3D deep models for action recognition with depth information. Signal Image and Video Processing. 12(6). 1197–1205. 23 indexed citations
10.
Keçeli, Ali Seydi, et al.. (2018). Classification of radiolarian fossil images with deep learning methods. 1–4. 7 indexed citations
11.
Keçeli, Ali Seydi & Aydın Kaya. (2017). Violent activity detection with transfer learning method. Electronics Letters. 53(15). 1047–1048. 33 indexed citations
12.
Kaya, Aydın, Ali Seydi Keçeli, Ahmet Burak Can, & Hasan Basri Çakmak. (2017). Cyclotorsion measurement using scleral blood vessels. Computers in Biology and Medicine. 87. 152–161. 3 indexed citations
13.
Keçeli, Ali Seydi, Aydın Kaya, & Ahmet Burak Can. (2017). Depth features to recognise dyadic interactions. IET Computer Vision. 12(3). 331–339. 2 indexed citations
14.
Keçeli, Ali Seydi, Aydın Kaya, & Ahmet Burak Can. (2017). Action recognition with skeletal volume and deep learning. 1–4. 4 indexed citations
15.
Keçeli, Ali Seydi, Ahmet Burak Can, & Aydın Kaya. (2017). A GPU-Based Approach for Automatic Segmentation of White Matter Lesions. IETE Journal of Research. 63(4). 461–472. 4 indexed citations
16.
Kaya, Aydın, et al.. (2017). Electrocardiographic Changes and Their Prognostic Effect in Patients with Acute Ischemic Stroke without Cardiac Etiology. Turkish Journal Of Neurology. 24(2). 137–142. 3 indexed citations
17.
Kaya, Aydın & Ahmet Burak Can. (2015). A weighted rule based method for predicting malignancy of pulmonary nodules by nodule characteristics. Journal of Biomedical Informatics. 56. 69–79. 36 indexed citations
18.
Kaya, Aydın, et al.. (2015). Early Clinical Predictors of Disability in Multiple Sclerosis. Turkish Journal Of Neurology. 21(1). 22–26.
19.
Yalıç, Hamdi Yalın, Ali Seydi Keçeli, & Aydın Kaya. (2013). On-Board Driver Assistance System for Lane Departure Warning and Vehicle Detection. 1(3). 132–136. 3 indexed citations
20.
Kaya, Aydın, Ahmet Burak Can, & Hasan Basri Çakmak. (2010). Designing a Pattern Stabilization Method Using Scleral Blood Vessels for Laser Eye Surgery. 39. 698–701. 2 indexed citations

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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