Enhancing crop productivity and sustainability through disease identification in maize leaves: Exploiting a large dataset with an advanced vision transformer model.

[BibT_eX]

[DOI]

Ishak Paçal

Expert Syst. Appl., March, 2024

2023

A comparative study of YOLO models and a transformer-based YOLOv5 model for mass detection in mammograms.

[BibT_eX]

[DOI]

Özkan Ufuk Nalbantoglu

Serap Dogan

Ishak Paçal

Meryem Altin Karagöz

Turkish J. Electr. Eng. Comput. Sci., November, 2023

Deep learning-based approaches for robust classification of cervical cancer.

[BibT_eX]

[DOI]

Ishak Paçal

Serhat Kiliçarslan

Neural Comput. Appl., September, 2023

Robust real-time polyp detection system design based on YOLO algorithms by optimizing activation functions and hyper-parameters with artificial bee colony (ABC).

[BibT_eX]

[DOI]

Özkan Ufuk Nalbantoglu

Seymanur Coskun

Omur Sahin

Dervis Karaboga

Expert Syst. Appl., July, 2023

Hyper-parameter optimization of deep learning architectures using artificial bee colony (ABC) algorithm for high performance real-time automatic colorectal cancer (CRC) polyp detection.

[BibT_eX]

[DOI]

Özkan Ufuk Nalbantoglu

Seymanur Coskun

Omur Sahin

Appl. Intell., June, 2023

2022

Derin öğrenme tabanlı gerçek zamanlı polip tespit yöntemlerinin geliştirilmesi ve incelenmesi (Development and investigation of deep learning based real-time polyp detection methods)

[BibT_eX]

[DOI]

Ishak Paçal

PhD thesis, 2022

An efficient real-time colonic polyp detection with YOLO algorithms trained by using negative samples and large datasets.

[BibT_eX]

[DOI]