Zobrazeno 1 - 10
of 1 303
pro vyhledávání: '"Pissas, A."'
Autor:
Pissas, Theodoros, Márquez-Neila, Pablo, Wolf, Sebastian, Zinkernagel, Martin, Sznitman, Raphael
This work explores the effectiveness of masked image modelling for learning representations of retinal OCT images. To this end, we leverage Masked Autoencoders (MAE), a simple and scalable method for self-supervised learning, to obtain a powerful and
Externí odkaz:
http://arxiv.org/abs/2405.14788
Autor:
Zbinden, Lukas, Doorenbos, Lars, Pissas, Theodoros, Huber, Adrian Thomas, Sznitman, Raphael, Márquez-Neila, Pablo
Semantic segmentation has made significant progress in recent years thanks to deep neural networks, but the common objective of generating a single segmentation output that accurately matches the image's content may not be suitable for safety-critica
Externí odkaz:
http://arxiv.org/abs/2303.08888
Autor:
Tziastoudi, Maria1 (AUTHOR) matziast@med.uth.gr, Pissas, Georgios1 (AUTHOR) gpissas@msn.com, Golfinopoulos, Spyridon1 (AUTHOR) spygolfin@yahoo.gr, Filippidis, Georgios1 (AUTHOR) gfilippid@yahoo.gr, Poulianiti, Christina1 (AUTHOR) christinepoulianiti@yahoo.gr, Tsironi, Evangelia E.2 (AUTHOR) e_tsironi@hotmail.com, Dardiotis, Efthimios3 (AUTHOR) edar@med.uth.gr, Eleftheriadis, Theodoros1 (AUTHOR) teleftheriadis@med.uth.gr, Stefanidis, Ioannis1 (AUTHOR) stefanid@uth.gr
Publikováno v:
International Journal of Molecular Sciences. Oct2024, Vol. 25 Issue 20, p10906. 7p.
Autor:
Angelopoulos, Panagiotis M., Oustadakis, Paschalis, Anastassakis, Georgios, Pissas, Michael, Taxiarchou, Maria
Publikováno v:
In Minerals Engineering October 2024 217
Autor:
Pissas, Georgios 1, Tziastoudi, Maria, Poulianiti, Christina, Polyzou Konsta, Maria Anna, Lykotsetas, Evangelos, Liakopoulos, Vasilios, Stefanidis, Ioannis, Eleftheriadis, Theodoros 1, ⁎
Publikováno v:
In International Immunopharmacology 10 January 2025 144
This work considers supervised contrastive learning for semantic segmentation. We apply contrastive learning to enhance the discriminative power of the multi-scale features extracted by semantic segmentation networks. Our key methodological insight i
Externí odkaz:
http://arxiv.org/abs/2203.13409
Autor:
Luengo, Imanol, Grammatikopoulou, Maria, Mohammadi, Rahim, Walsh, Chris, Nwoye, Chinedu Innocent, Alapatt, Deepak, Padoy, Nicolas, Ni, Zhen-Liang, Fan, Chen-Chen, Bian, Gui-Bin, Hou, Zeng-Guang, Ha, Heonjin, Wang, Jiacheng, Wang, Haojie, Guo, Dong, Wang, Lu, Wang, Guotai, Islam, Mobarakol, Giddwani, Bharat, Hongliang, Ren, Pissas, Theodoros, Ravasio, Claudio, Huber, Martin, Birch, Jeremy, Rio, Joan M. Nunez Do, da Cruz, Lyndon, Bergeles, Christos, Chen, Hongyu, Jia, Fucang, KumarTomar, Nikhil, Jha, Debesh, Riegler, Michael A., Halvorsen, Pal, Bano, Sophia, Vaghela, Uddhav, Hong, Jianyuan, Ye, Haili, Huang, Feihong, Wang, Da-Han, Stoyanov, Danail
Surgical scene segmentation is essential for anatomy and instrument localization which can be further used to assess tissue-instrument interactions during a surgical procedure. In 2017, the Challenge on Automatic Tool Annotation for cataRACT Surgery
Externí odkaz:
http://arxiv.org/abs/2110.10965
Our work proposes neural network design choices that set the state-of-the-art on a challenging public benchmark on cataract surgery, CaDIS. Our methodology achieves strong performance across three semantic segmentation tasks with increasingly granula
Externí odkaz:
http://arxiv.org/abs/2108.06119
Publikováno v:
Communications Physics, Vol 6, Iss 1, Pp 1-10 (2023)
Abstract In the model manganese perovskites La1−x Ca x MnO3, several important phenomena have been observed, including ferromagnetic metallic/insulating states, colossal magnetoresistance effects, and charge- and orbital-ordered states. In the past
Externí odkaz:
https://doaj.org/article/324ca1b7d8c84b0c9a2331f4860f5872
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