Ahmet Saygili

According to our database, Ahmet Saygili authored at least 16 papers between 2013 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

MOD-YOLOv8: a new YOLOv8-based model for meniscal tear detection in knee MRI.

Mehmet Ali Simsek, Hadi Sasani, Yasar Mahsut Dinçel, Ahmet Saygili, Fatih Uysal, Ahmet Sertbas

PeerJ Comput. Sci., 2026

2025

Hybrid few-shot learning and vision transformer approaches for the diagnosis of Monkeypox.

Hilal Güven, Ahmet Saygili

Signal Image Video Process., December, 2025

Deep learning-based histopathological classification of breast tumors: a multi-magnification approach with state-of-the-art models.

Gizem Irmak, Ahmet Saygili

Signal Image Video Process., July, 2025

Performance of machine learning methods for cattle identification and recognition from retinal images.

Pinar Cihan, Ahmet Saygili, Muhammed Akyüzlü, Nihat Eren Özmen, Celal Sahin Ermutlu, Ugur Aydin, Alican Yilmaz, Özgür Aksoy

Appl. Intell., April, 2025

Enhancing Retinal Disease Detection With the Swin Transformer: A Comprehensive Comparative Analysis.

Ahmet Saygili, Ömer Mutlu Atici

Concurr. Comput. Pract. Exp., 2025

2024

A new approach for automatic classification of non-Hodgkin lymphoma using deep learning and classical learning methods on histopathological images.

Emine Özgür, Ahmet Saygili

Neural Comput. Appl., November, 2024

CattNIS: Novel identification system of cattle with retinal images based on feature matching method.

Ahmet Saygili, Pinar Cihan, Celal Sahin Ermutlu, Ugur Aydin, Özgür Aksoy

Comput. Electron. Agric., 2024

AI-aided cardiovascular disease diagnosis in cattle from retinal images: Machine learning vs. deep learning models.

Pinar Cihan, Ahmet Saygili, Celal Sahin Ermutlu, Ugur Aydin, Özgür Aksoy

Comput. Electron. Agric., 2024

2021

A new approach for computer-aided detection of coronavirus (COVID-19) from CT and X-ray images using machine learning methods.

Ahmet Saygili

Appl. Soft Comput., 2021

2019

An efficient and fast computer-aided method for fully automated diagnosis of meniscal tears from magnetic resonance images.

Ahmet Saygili, Songül Albayrak

Artif. Intell. Medicine, 2019

2018

Meniscus tear classification using histogram of oriented gradients in knee MR images.

Ahmet Saygili, Songul Albayrak

Proceedings of the 26th Signal Processing and Communications Applications Conference, 2018

2017

MR görüntülerinde menisküslerin segmentasyonu ve menisküs yırtıklarının tespiti (Meniscus segmentation and detection of meniscus tears in MR images)

Ahmet Saygili

PhD thesis, 2017

Meniscus segmentation and tear detection in the knee MR images by fuzzy c-means method.

Ahmet Saygili, Songul Albayrak

Proceedings of the 25th Signal Processing and Communications Applications Conference, 2017

2016

Automatic detection of meniscal area in the knee MR images.

Ahmet Saygili, Heysem Kaya, Songul Albayrak

Proceedings of the 24th Signal Processing and Communication Application Conference, 2016

2015

Comparative analysis of codeword representation by clustering methods for the classification of histological tissue types.

Ahmet Saygili, Gunalp Uysal, Gokhan Bilgin

Proceedings of the Eighth International Conference on Machine Vision, 2015

2013

Faculty of engineering students' success analysis with clustering methods.

Ahmet Saygili, Songul Albayrak

Proceedings of the 21st Signal Processing and Communications Applications Conference, 2013