Items where Author is "Yavuz, Mehmet Can"

Article

Ali Ahmed, Sara Atito and Yavuz, Mehmet Can and Şen, Mehmet Umut and Gülşen, Fatih and Tutar, Onur and Korkmazer, Bora and Samancı, Cesur and Şirolu, Sabri and Hamid, Rauf and Eryürekli, Ali Ergun and Mammadov, Toghrul and Yanıkoğlu, Berrin (2022) Comparison and ensemble of 2D and 3D approaches for COVID-19 detection in CT images. Neurocomputing, 488 . pp. 457-469. ISSN 0925-2312 (Print) 1872-8286 (Online)

Papers in Conference Proceedings

Yavuz, Mehmet Can and Yanıkoğlu, Berrin (2022) VCL-PL: semi-supervised learning from noisy web data with variational contrastive learning. In: 26th International Conference on Pattern Recognition (ICPR), Montreal, Canada

Yavuz, Mehmet Can (2021) Analyses of dramatic network simulations by using Markov chains. In: 8th International Conference on Behavioral and Social Computing (BESC), Doha, Qatar

Yavuz, Mehmet Can and Ali Ahmed, Sara Atito and Kısaağa, Mehmet Efe and Ocak, Hasan and Yanıkoğlu, Berrin (2021) YFCC-CelebA face attributes datasets [YFCC-CelebA yüz özellikleri veri setleri]. In: 29th Signal Processing and Communications Applications Conference (SIU), Istanbul, Turkey

Yavuz, Mehmet Can (2021) Analyses of character emotions in dramatic works by using emolex unigrams. In: 7th Italian Conference on Computational Linguistics, CLiC-it 2020, Bologna, Italy

Yavuz, Mehmet Can (2020) Analyses of character networks in dramatic works by using graphs. In: 7th International Conference on Behavioural and Social Computing (BESC), Bournemouth, United Kingdom

Yavuz, Mehmet Can (2020) Analyses of characters in dramatic works by using document embeddings. In: 2020 Workshop on Digital Humanities and Natural Language Processing, DH and NLP 2020, Evora

Yavuz, Mehmet Can (2019) Analyses of literary texts by using statistical inference methods. In: 6th Italian Conference on Computational Linguistics, CLiC-it 2019, Bari, Italy

Thesis

Yavuz, Mehmet Can (2023) Self- And Weakly- Supervised Deep Learning Methods With Applications In Biometric And Biomedical Data. [Thesis]