Zobrazeno 1 - 10
of 153
pro vyhledávání: '"HAZIM KEMAL EKENEL"'
Autor:
Pedro C. Neto, Fadi Boutros, Joao Ribeiro Pinto, Naser Damer, Ana F. Sequeira, Jaime S. Cardoso, Messaoud Bengherabi, Abderaouf Bousnat, Sana Boucheta, Nesrine Hebbadj, Mustafa Ekrem Erakin, Ugur Demir, Hazim Kemal Ekenel, Pedro Beber De Queiroz Vidal, David Menotti
This work summarizes the IJCB Occluded Face Recognition Competition 2022 (IJCB-OCFR-2022) embraced by the 2022 International Joint Conference on Biometrics (IJCB 2022). OCFR-2022 attracted a total of 3 participating teams, from academia. Eventually,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b650e04ffb5bc0b189ef2d0404aa9e6
http://arxiv.org/abs/2208.02760
http://arxiv.org/abs/2208.02760
Publikováno v:
Multimedia Tools and Applications. 81:22695-22713
In this paper, we present a multimodal, multitask deep convolutional neural network framework for age and gender classification. In the developed framework, we have employed two different biometric modalities: ear and profile face. We have explored t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de34ad7b38f859cd967a0686625d83ca
https://doi.org/10.1007/s11042-021-10630-8
https://doi.org/10.1007/s11042-021-10630-8
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d26013502b773cd6b5d0685e23075d47
https://doi.org/10.1109/cvprw56347.2022.00083
https://doi.org/10.1109/cvprw56347.2022.00083
Autor:
Seymanur Akti, Alperen Kantarci, Mustafa Ekrem Erakin, Furkan Cinik, Tolga Timirci, Hazim Kemal Ekenel
Publikováno v:
2022 30th Signal Processing and Communications Applications Conference (SIU).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dfba1d7fd0aaa3fef7cae67e3363e286
https://doi.org/10.1109/siu55565.2022.9864931
https://doi.org/10.1109/siu55565.2022.9864931
Publikováno v:
2022 30th Signal Processing and Communications Applications Conference (SIU).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ea7c5c2d24f8728a90c4190037daf5d
https://doi.org/10.1109/siu55565.2022.9864862
https://doi.org/10.1109/siu55565.2022.9864862
Autor:
Ali Karatana, Hazim Kemal Ekenel
Publikováno v:
2022 30th Signal Processing and Communications Applications Conference (SIU).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::978ae5c7616db17af1bdaa75c218335f
https://doi.org/10.1109/siu55565.2022.9864971
https://doi.org/10.1109/siu55565.2022.9864971
Autor:
Claudiu Musat, Hazim Kemal Ekenel, Jean-Philippe Thiran, Max Basler, Mohammad Saeed Rad, Urs-Viktor Marti, Behzad Bozorgtabar
Publikováno v:
Neurocomputing. 398:304-313
Despite significant progress toward super resolving more realistic images by deeper convolutional neural networks (CNNs), reconstructing fine and natural textures still remains a challenging problem. Recent works on single image super resolution (SIS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53e7575d019c21667d7b644bdc8fa68d
https://doi.org/10.1016/j.neucom.2019.07.107
https://doi.org/10.1016/j.neucom.2019.07.107
Autor:
Fabio Valerio Massoli, Fabrizio Falchi, Alperen Kantarci, Seymanur Akti, Hazim Kemal Ekenel, Giuseppe Amato
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems 33 (2021): 2313–2323. doi:10.1109/TNNLS.2021.3130074
Anomalies are ubiquitous in all scientific fields and can express an unexpected event due to incomplete knowledge about the data distribution or an unknown process that suddenly comes into play and distorts observations. Due to such events' rarity, t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e206fba5211f7be0a1959f5387ab51dc
https://pubmed.ncbi.nlm.nih.gov/34874873
https://pubmed.ncbi.nlm.nih.gov/34874873
Publikováno v:
2021 6th International Conference on Computer Science and Engineering (UBMK).
Deep learning models require large amount of training data to reach high accuracies. However, labeling large volumes of training data is a labor-intensive and time-consuming process. Active learning is an approach that seeks to maximize the performan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1881ec5b4d2780d1cd730b530ece03eb
https://doi.org/10.1109/ubmk52708.2021.9559028
https://doi.org/10.1109/ubmk52708.2021.9559028
Autor:
Hazim Kemal Ekenel, Selin Gok Isik
Publikováno v:
2021 6th International Conference on Computer Science and Engineering (UBMK).
Today, many different biometric features are used for human identification. Unlike biometric features, such as eye, iris, ear, and fingerprint, gait biometrics enables recognition from long distance and low resolution images. In this paper, different
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7f05e1d6533659b06c674e3fcf402eb
https://doi.org/10.1109/ubmk52708.2021.9559026
https://doi.org/10.1109/ubmk52708.2021.9559026