Erkut ARICAN

Journals

2025:

• Obesity Classification: A Comparative Study of Machine Learning Models Excluding Weight and Height Data, A.C. GENC, E. ARICAN – Revista da Associação Médica Brasileira

2022:

• An RGB-D descriptor for object classification, E ARICAN, T AYDIN – SCIENCE AND TECHNOLOGY (ROMJIST) 25 (3-4), 338-349

2019:

• 3D Object Detection Using a New Descriptor with RGB-D, E Arıcan, T Aydın – Bilge International Journal of Science and Technology Research 3 (1), 58-62

2016:

• Comparing prediction algorithms in disorganized data, E Arıcan, A Karahoca – Global Journal of Computer Sciences: Theory and Research 6 (2), 26-35

Conferences

2013:

• Çok Ölçekli Panoramik Eklendirilmiş Gerçeklik – Signal Processing and Communications Applications Conference (SIU), 2013 21st
• MULTI-SCALE PANORAMIC AUGMENTED REALITY WITH AUTOMATIC IMAGE SCALING – 3rd International Symposium on Computing in Science & Engineering

2016:

• Automatic scale and image selection for panoramic images – 2016 24th Signal Processing and Communication Application Conference (SIU)
• Efficient multi-scale scene representation for augmented reality applications – International Conference on Engineering and Natural Science (ICENS)

2017:

• Object Detection With RGB-D Data Using Depth Oriented Gradients – International Conference on Engineering and Natural Sciences (ICENS)

2018:

• A New Descriptor for 3D Object Detection using RGB-D – International Conference on Science and Technology

2022:

• Comparing Fusion Methods for 3D Object Detection – Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation: Proceedings of the INFUS 2021 Conference

Theses Supervised

2024:

• Mohammed B.M. MOHAMMED, Impact of Stylization on Deep Face Recognition Networks Using Digital Images, Bahcesehir University
• Ahmed Cihad GENÇ, Beyond BMI: Comparative Analysis of Machine Learning Models for Obesity Classification Without Height and Weight Data, Bahcesehir University
• Khaled AL HARIRI,  Enhancing Image-to-Image Translation: A Novel Conditional Generative Adversarial Network Approach with U-Net and ResNet Combination, Bahcesehir University