Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Giorgos Kordopatis-Zilos"'
Autor:
Nikos Lazaridis, Kostas Georgiadis, Fotis Kalaganis, Giorgos Kordopatis-Zilos, Symeon Papadopoulos, Spiros Nikolopoulos, Ioannis Kompatsiaris
Publikováno v:
IEEE Access, Vol 12, Pp 129705-129716 (2024)
The Transformer revolutionized Natural Language Processing and Computer Vision by effectively capturing contextual relationships in sequential data through its attention mechanism. While Transformers have been explored sufficiently in traditional com
Externí odkaz:
https://doaj.org/article/682bb2794dfb4408baf1f72c1a7001dc
In this paper we introduce InDistill, a model compression approach that combines knowledge distillation and channel pruning in a unified framework for the transfer of the critical information flow paths from a heavyweight teacher to a lightweight stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f79023da783d180ee040756242286ca
Autor:
Maria Siopi, Giorgos Kordopatis-Zilos, Polychronis Charitidis, Ioannis Kompatsiaris, Symeon Papadopoulos
Publikováno v:
MultiMedia Modeling ISBN: 9783031278174
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0fc238f4d114b7e018f4eb05b011e3d9
https://doi.org/10.1007/978-3-031-27818-1_50
https://doi.org/10.1007/978-3-031-27818-1_50
Autor:
Giorgos Kordopatis-Zilos, Christos Tzelepis, Ioannis (Yiannis) Kompatsiaris, Symeon Papadopoulos, Ioannis Patras
In this paper, we address the problem of high performance and computationally efficient content-based video retrieval in large-scale datasets. Current methods typically propose either: (i) fine-grained approaches employing spatio-temporal representat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a5fc759622912f73c49af0b9f967452
Autor:
Bogdan Ionescu, Giorgos Kordopatis-Zilos, Adrian Popescu, Luca Cuccovillo, Symeon Papadopoulos
Publikováno v:
Proceedings of the 2022 International Conference on Multimedia Retrieval.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68f5679ec66d13324eb01a9a9f3078ec
https://doi.org/10.1145/3512527.3531440
https://doi.org/10.1145/3512527.3531440
Publikováno v:
MultiMedia Modeling ISBN: 9783030983543
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a1813af07c31683f97d688e7368827d
https://doi.org/10.1007/978-3-030-98355-0_31
https://doi.org/10.1007/978-3-030-98355-0_31
Autor:
Kostas Georgiadis, Elisavet Chatzilari, Savvas Tortopidis, Panagiotis Migkotzidis, Ioannis Kompatsiaris, Valasia Panakidou, Giorgos Kordopatis-Zilos, Symeon Papadopoulos, Kyriakos Pantouvakis, Fotis Kalaganis, Spiros Nikolopoulos
Publikováno v:
PETRA
Product recognition is a task that receives continuous attention by the computer vision/deep learning community mainly with the scope of providing robust solutions for automatic checkout supermarkets. One of the main challenges is the lack of images
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d52f6fb6b59bcc2048fdf95c3e3efe1
https://doi.org/10.1145/3453892.3453894
https://doi.org/10.1145/3453892.3453894
Publikováno v:
Proceedings of the 2021 International Conference on Multimedia Retrieval
ICMR
ICMR
In this paper, we address the problem of global-scale image geolocation, proposing a mixed classification-retrieval scheme. Unlike other methods that strictly tackle the problem as a classification or retrieval task, we combine the two practices in a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a72cf47df8a682c81e2451b844896adc
http://arxiv.org/abs/2105.07645
http://arxiv.org/abs/2105.07645
Autor:
Giorgos Kordopatis-Zilos, Symeon Papadopoulos, Ioannis Kompatsiaris, Andreas L. Symeonidis, Pavlos Avgoustinakis
Publikováno v:
ICPR
2020 25th International Conference on Pattern Recognition (ICPR)
2020 25th International Conference on Pattern Recognition (ICPR)
In this work, we address the problem of audio-based near-duplicate video retrieval. We propose the Audio Similarity Learning (AuSiL) approach that effectively captures temporal patterns of audio similarity between video pairs. For the robust similari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42df8c828d123cdfe8b0ecc646204eb7
Publikováno v:
Proceedings of the IEEE. 105:1971-1986
The large-scale availability of user-generated content in social media platforms has recently opened up new possibilities for studying and understanding the geospatial aspects of real-world phenomena and events. Yet, the large majority of user-genera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f7c659cb0b9631556c3824869108fb39
https://doi.org/10.1109/jproc.2017.2688799
https://doi.org/10.1109/jproc.2017.2688799