Browsing by Author "Çakar Tuna"
Now showing items 1-6 of 6
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Dog Walker Segmentation
Ercan Alperen; Karan Baris; Çakar Tuna (IEEE, 2022)In this study dog walkers were separated into clusters according to walkers' walk habits. Due to the fact that the distributions were non-normal, normalization algorithms were applied before the onset of clustering. After ... -
Model for Estimating the Probability of a Customer to Have a Transaction
Sayar Alperen; Bozkan Tunahan; Çakar Tuna; Ertugrul Seyit (IEEE, 2022)In this study, it is aimed to estimate the probability of a customer who comes to the institution for the first time to make a transaction in the next 3 months, using data-driven machine learning models, in order to provide ... -
Modeling Consumer Creditworthiness via Psychometric Scale and Machine Learning
Sahin Türkay; Çakar Tuna; Bozkan Tunahan; Ertugrul Seyit; Sayar Alperen (IEEE, 2022)Although the predictive power of economic metrics to detect the creditworthiness of the customers is high, there is a rising interest in the integration of cognitive, psychological, behavioral, alternative, and demographic ... -
Predicting Animal Behaviours: Physical and Behavioural Classification Of Dog Walking Levels
Özen Guris; Karan Baris; Çakar Tuna (IEEE, 2022)Methods of predicting canine behaviour is an area covered by canine behaviour experts. This study aims to predict the behaviour of dogs during walking based on available information about dogs. In this data-driven project ... -
SSQEM: Semi-Supervised Quantum Error Mitigation
Sayar, Alperen; Arslan Suayb S.; Çakar Tuna (IEEE, 2022)One of the fundamental obstacles for quantum computation (especially in noisy intermediate-scale quantum (NISQ) era) to be a near-term reality is the manufacturing gate/measurement technologies that make the system state ... -
Steel Surface Defect Classification Via Deep Learning
Tunal Mustafa Mert; Yildiz Ahmet; Çakar Tuna (IEEE, 2022)Deep learning and image processing methods have taken place in many parts of our lives, as well as in the quality control stages of production lines. The aim of this study is to train and use a deep learning model to improve ...
