Yayınlarım

Dergi Yayınları

2025:

  • A Hybrid Conditional GAN Design for Image-to-Image Translation Integrating U-Net and ResNet, K Al Hariri, M Paşaoğlu, E Arıcan – Firat University Journal of Experimental and Computational Engineering
  • Enhanced E-commerce decision-making through sentiment analysis using machine learning-based approaches and IoT, Y Filahi, OM Gul, A Elghirani, E Arican, IB Parlak, S Kadry, K Karpouzis – PloS one
  • Obesity Classification: A Comparative Study of Machine Learning Models Excluding Weight and Height Data, AC Genc, E Arıcan – Revista da Associação Médica Brasileira

2022:

2019:

2016:

Konferans Sunumları

2025:

2024:

  • Optimizing recommendation systems by fusion of KNN, singular value decomposition, and XGBoost for enhanced performance, M Paşaoğlu, E Arıcan – 2024 9th International Conference on Computer Science and Engineering (UBMK)
  • Advanced Computer Vision Techniques for Reliable Gender Determination in Budgerigars (Melopsittacus Undulatus), A Denknalbant, EI Cemalcılar, M Ahangari, A Saidburkhan, AZ Ghazani, E Arıcan – 2024 9th International Conference on Computer Science and Engineering (UBMK)
  • Integrating multiple methodologies, Segment anything model and Alexnet, for enhanced accuracy in garbage classification, O Kibar, MG Bakır, B Taşdemir, NAA Fadlallah, E Arıcan – 2024 Innovations in Intelligent Systems and Applications Conference (ASYU)
  • A new implementation with combining mixture of UNet and ResNet type architectures for image-to-image translation, E Arican, KA Hariri – 33rd European Conference on Operational Research

2021:

2018:

2017:

2016:

2013:

Yönetilen Tezler

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