Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Apostolos, Axenopoulos"'
Autor:
Georgios Kalitsios, Lazaros Lazaridis, Athanasios Psaltis, Apostolos Axenopoulos, Petros Daras
Publikováno v:
2022 4th International Conference on Robotics and Computer Vision (ICRCV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a8d9567f5276ba12a478d1a72ed62be
https://doi.org/10.1109/icrcv55858.2022.9953178
https://doi.org/10.1109/icrcv55858.2022.9953178
Autor:
Spyros Petrakis, Stelios K. Mylonas, Sotiris Katsamakas, Kostas Stamatopoulos, Apostolos Axenopoulos, Ioannis Gkekas, Petros Daras
Publikováno v:
BIBE
2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE)
2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE)
Drug discovery involves extremely costly and time consuming procedures and can be significantly benefited by computational approaches, such as virtual screening (VS). Structure-based VS relies on scoring functions which aim to evaluate the binding of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41754a2ec5f72d60b6f563922f679cd5
https://doi.org/10.1109/bibe50027.2020.00030
https://doi.org/10.1109/bibe50027.2020.00030
Publikováno v:
Bioinformatics (Oxford, England).
Motivation The knowledge of potentially druggable binding sites on proteins is an important preliminary step toward the discovery of novel drugs. The computational prediction of such areas can be boosted by following the recent major advances in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7878820747dbb87574e8e8c70e7fed6
https://pubmed.ncbi.nlm.nih.gov/33471069
https://pubmed.ncbi.nlm.nih.gov/33471069
Publikováno v:
Intelligent Systems Reference Library ISBN: 9783030427481
The main goal of this chapter is to develop a system for automatic protein classification. Proteins are classified using CNNs trained on ImageNet, which are tuned using a set of multiview 2D images of 3D protein structures generated by Jmol, which is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::daeed9d79baf756e83661386e8d454f6
https://doi.org/10.1007/978-3-030-42750-4_9
https://doi.org/10.1007/978-3-030-42750-4_9
Autor:
Ziming Liu, Weiping Yu, Zehui Gong, Yan Ding, Fanman Meng, Qizhang Lin, Dheeraj Reddy Pailla, Hongliang Li, Yan Luo, Pengfei Zhu, Murari Mandal, Zhiwei Wei, Junwen Pan, Apostolos Axenopoulos, Mubarak Shah, Michael Schleiss, Jong Hwan Ko, Qinghua Hu, Yongwoo Kim, Sai Wang, Hansheng Chen, Heng Fan, Zichen Song, Chengzhen Duan, Xiaogang Jia, Haibin Ling, Ming-Hsuan Yang, Jungyeop Yoo, Qiu Shi, Hao Zhou, Bin Dong, Xingjie Zhao, Athanasios Psaltis, Chen Chen, Zhongjie Fan, Wenxiang Lin, Yuehan Yao, Joochan Lee, Pratik Narang, Yu Sun, Weida Qin, Sarvesh Mehta, Qiong Liu, Guosheng Zhang, Zhenyu Xu, Petros Daras, Minjian Zhang, Longyin Wen, Jun Yu, Guangyu Gao, Yuyao Huang, Lu Xiong, Jingkai Zhou, Mingyu Liu, Xi Zhao, Yang Xiao, Xuanxin Liu, Yi Wang, Heqian Qiu, Chongyang Zhang, Lars Sommer, Taijin Zhao, Faizan Farooq Khan, Wei Tian, Jincai Cui, Yingjie Liu, Shuai Li, Zhiguo Cao, Shuqin Huang, Ting Sun, Haonian Xie, Ioannis Athanasiadis, Zhipeng Luo, Dawei Du, Wei Guo, Rohit Ramaprasad, Xin He, Sungtae Moon, Arne Schumann, Ayush Jain, Changlin Li, Dong Yin, Daniel Stadler
Publikováno v:
Computer Vision – ECCV 2020 Workshops ISBN: 9783030668228
ECCV Workshops (4)
ECCV Workshops (4)
The Vision Meets Drone Object Detection in Image Challenge (VisDrone-DET 2020) is the third annual object detector benchmarking activity. Compared with the previous VisDrone-DET 2018 and VisDrone-DET 2019 challenges, many submitted object detectors e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::609bce22589ccd0e26af40d7785642be
https://doi.org/10.1007/978-3-030-66823-5_42
https://doi.org/10.1007/978-3-030-66823-5_42
Autor:
Florent Langenfeld, David Hunter, Matthieu Montes, Karim Hammoudi, Daisuke Kihara, Feryal Windal, Yu-Kun Lai, Ekpo Otu, Paul L. Rosin, Stelios K. Mylonas, Petros Daras, Apostolos Axenopoulos, Halim Benhabiles, Reyer Zwiggelaar, Andrea Giachetti, Charles Christoffer, Adnane Cabani, Tunde Aderinwale, Yuxu Peng, Yonghuai Liu, Mahmoud Melkemi, Genki Terashi
Publikováno v:
Computers and Graphics
Computers and Graphics, Elsevier, 2020, 91, pp.189-198. ⟨10.1016/j.cag.2020.07.013⟩
Computers & Graphics
Computers and Graphics, 2020, 91, pp.189-198. ⟨10.1016/j.cag.2020.07.013⟩
Computers and Graphics, Elsevier, 2020, 91, pp.189-198. ⟨10.1016/j.cag.2020.07.013⟩
Computers & Graphics
Computers and Graphics, 2020, 91, pp.189-198. ⟨10.1016/j.cag.2020.07.013⟩
[#17491] article suite à une conférence orale: 13th EG Euroworkshop on 3D object retrieval, 3DOR 2020, Graz, Austria, september 4-5, 2020; International audience; Proteins are natural modular objects usually composed of several domains, each domain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca77de2112dc6449e41847eefc6ba5d9
http://hdl.handle.net/11562/1030083
http://hdl.handle.net/11562/1030083
Autor:
Michael G. Strintzis, Dimitrios Tzovaras, Apostolos Axenopoulos, Petros Daras, Dimitrios Zarpalas
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2007 (2007)
This paper presents a novel methodology for content-based search and retrieval of 3D objects. After proper positioning of the 3D objects using translation and scaling, a set of functionals is applied to the 3D model producing a new domain of concentr
Externí odkaz:
https://doaj.org/article/230fec0a7bd54f57b62b90a55bcc067a
Publikováno v:
ICE/ITMC
Deep learning approaches have recently proven their effectiveness in the task of image Super Resolution (SR). In most cases, very deep structures have been adopted to increase the models’ performance, leading to neural networks with a high paramete
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27da809e937a32d58bbb880af23ee029
https://doi.org/10.1109/ice.2019.8792573
https://doi.org/10.1109/ice.2019.8792573
Autor:
Florent, Langenfeld, Apostolos, Axenopoulos, Halim, Benhabiles, Petros, Daras, Giachetti, Andrea, Xusi, Han, Karim, Hammoudi, Daisuke, Kihara, Lai, Tuan M., Haiguang, Liu, Mahmoud, Melkemi, Mylonas, Stelios K., Genki, Terashi, Yufan, Wang, Feryal, Windal, Matthieu, Montes
This track aimed at retrieving protein evolutionary classification based on their surfaces meshes only. Given that proteins are dynamic, non-rigid objects and that evolution tends to conserve patterns related to their activity and function, this trac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94cbf0a44255309c8dcc4a01144a05a6
Autor:
Petros Daras, Theodoros Semertzidis, Apostolos Axenopoulos, Aikaterini Nikolaidou, Michalis Lazaridis
Publikováno v:
KEOD
It is a challenge to aggregate and analyze data from heterogeneous social media sources not only for businesses and organizations but also for Law Enforcement Agencies. The latter’s core objectives are to monitor criminal and terrorist related acti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8be1d4827c4e40372bce8072edac5194
https://doi.org/10.5220/0008347803430350
https://doi.org/10.5220/0008347803430350