Applied Artificial Intelligence

The Applied Artificial Intelligence Research Group, operating within the Departments of Computer Engineering and Software Engineering, is composed of expert researchers specializing in deep learning, artificial intelligence, machine learning, and pattern recognition, and conducts research across various interdisciplinary fields. The group is also open to collaborations.

News

12/19/2024

ASYU2024 Konferansında Özel Oturum
10/16/2024

Makalemiz Elsevier'in Engineering Applications of Artificial Intelligence (Q1) Dergisinde Kabul Edildi.
10/16/2024

3 bildirimiz 47. Uluslararası Telekomünikasyon ve Sinyal İşleme Konferansı'nda (TSP 2024) yayımlandı.
10/16/2024

Makalemiz Springer'in Signal, Image and Video Processing (Q2) Dergisinde Kabul Edildi.
10/16/2024

TÜBİTAK 3501-Kariyer Geliştirme Programı bünyesinde kabul edilen yeni projemiz.
10/16/2024

Makalemiz Springer'in Medical & Biological Engineering & Computing (Q2) Dergisinde Kabul Edildi.
10/16/2024

Makalemiz Springer'in Neural Computing and Applications Dergisinde Kabul Edildi
10/16/2024

Makalemiz Elsevier'in Expert Systems with Applications (Q1) Dergisinde Kabul Edildi.

Recent Publications

Parasite Classification in Biomedical Imaging Utilizing Vision Mamba

YURDUSEVER K. C., Kablan E. B., AYAS S.
9th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2025, Gaziantep, Turkey, 27 - 28 June 2025, (Full Text)

Advancing Colorectal Polyp Detection and Segmentation Through YOLOv11 Architecture

Gülsoy T., Kanca Gülsoy E., Baykal Kablan E., Ayas S.
2025 9th International Symposium on Innovative Approaches in Smart Technologies (ISAS), Gaziantep, Turkey, 27 - 28 June 2025, pp.1-7, (Full Text)

Remote Sensing Scene Image Classification with Swin Transformer-Based Transfer Learning

Kanca Gülsoy E., Gülsoy T., Baykal Kablan E., Ayas S.
2025 9th International Symposium on Innovative Approaches in Smart Technologies (ISAS), Gaziantep, Turkey, 27 - 28 June 2025, pp.1-6, (Full Text)

Detecting audio splicing forgery: A noise-robust approach with Swin Transformer and cochleagram

GÜLSOY T., KANCA GÜLSOY E., Ustubioglu A., ÜSTÜBİOĞLU B., BAYKAL KABLAN E., AYAS S., et al.
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS, vol.93, 2025 (SCI-Expanded, Scopus)

Automatic Botox Injection Points Detection Based on Deep Learning

Gülsoy T., Baykal Kablan E., Ayas S., Baykal Selçuk L., Aksu Arıca D.
2025 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA), Ankara, Turkey, 23 - 24 May 2025, pp.1-8, (Full Text)

Investigation of The Performance of Yolov5 Models In The Detection and Classification of Shoulder Implants Using X-Ray Images

Kablan E. B.
Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi, vol.27, no.79, pp.99-109, 2025 (TRDizin)

Enhancing the adversarial robustness in medical image classification: exploring adversarial machine learning with vision transformers-based models

Kanca E., Ayas S., Baykal Kablan E., Ekinci M.
NEURAL COMPUTING AND APPLICATIONS, vol.36, pp.1-19, 2025 (SCI-Expanded, Scopus)

Deep Learning-Based Audio Splicing Forgery Detection Using PVTv2 Transformer

Kanca E., Gülsoy T., Üstübioğlu A., Üstübioğlu B., Ayas S., Baykal Kablan E., et al.
2024 Innovations in Intelligent Systems and Applications Conference (ASYU), Ankara, Turkey, 16 - 18 October 2024, pp.1-5, (Full Text)

Generating Robust Adversarial Images in Medical Image Classification using GANs

Kanca E., Gülsoy T., Ayas S., Baykal Kablan E.
2024 Innovations in Intelligent Systems and Applications Conference (ASYU), Ankara, Turkey, 16 - 18 October 2024, pp.1-5, (Full Text)

Evaluating and enhancing the robustness of vision transformers against adversarial attacks in medical imaging

KANCA GÜLSOY E., AYAS S., BAYKAL KABLAN E., EKİNCİ M.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, vol.63, pp.673-690, 2025 (SCI-Expanded, Scopus)