Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Niki Martinel"'
Publikováno v:
Information, Vol 14, Iss 5, p 296 (2023)
Blind image super-resolution (Blind-SR) is the process of leveraging a low-resolution (LR) image, with unknown degradation, to generate its high-resolution (HR) version. Most of the existing blind SR techniques use a degradation estimator network to
Externí odkaz:
https://doaj.org/article/0be1885140054dceb1297cb40ed6dcb3
Autor:
Niki Martinel
Publikováno v:
ELCVIA Electronic Letters on Computer Vision and Image Analysis, Vol 14, Iss 3 (2015)
In automated video surveillance applications, presenting the useful information to the human operators is a challenging task. Current systems usually require a prohibitive amount of human resources and lead to a quick decrease of the attention of the
Externí odkaz:
https://doaj.org/article/22d62d396bf341e4a49dbbe83a64cf6e
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031250743
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0dcb63628590c18c7db579230097e195
https://doi.org/10.1007/978-3-031-25075-0_25
https://doi.org/10.1007/978-3-031-25075-0_25
Publikováno v:
IEEE Transactions on Industrial Informatics. 18:87-96
Vehicle reidentification has seen increasing interest, thanks to its fundamental impact on intelligent surveillance systems and smart transportation. The visual data acquired from monitoring camera networks come with severe challenges, including occl
Publikováno v:
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society. 102
Convolutional neural networks (CNNs) applied to magnetic resonance imaging (MRI) have demonstrated their ability in the automatic diagnosis of knee injuries. Despite the promising results, the currently available solutions do not take into account th
Autor:
Philip H. S. Torr, Haitao Zhang, Bin Yan, Ziyi Cheng, Fahad Shahbaz Khan, Shoumeng Qiu, Bineng Zhong, Ondrej Drbohlav, Bo Liu, Ozgun Cirakman, Kristian Simonato, Danda Pani Paudel, Xin Chen, Xiangyuan Lan, Wei Lu, Martin Danelljan, Felix Järemo Lawin, Qing Guo, Luka Čehovin Zajc, Christoph Mayer, Xiao Ke, Wankou Yang, Yanyan Huang, Xiaoning Song, Dong Wang, Felix Juefei-Xu, Xue-Feng Zhu, Guangting Wang, Jingen Liu, Jani Käpylä, Ales Leonardis, Christian Micheloni, Paul Voigtlaender, Yu-Chen Chiu, Lijun Wang, Shengyong Chen, Linyuan Wang, Shaochuan Zhao, Ling Shao, Yong Wang, Li Liu, Xiaoyun Yang, Liangliang Wang, Rongrong Ji, Gustavo Fernandez, Bilge Gunsel, Xingping Dong, Fei Xie, Jun Yin, Zhangyong Tang, Michael Felsberg, Aravindh Rajiv, Andreas Robinson, Miao Cheng, Mohana Murali Dasari, Josef Kittler, Chang Liu, Wencheng Han, Zhongqun Zhang, Yuezhou Li, Bedirhan Uzun, Roman Pflugfelder, Jinyu Yang, Yu Ye, Goutam Bhat, Kangkai Zhang, Hui Li, Jiri Matas, Mohamed H. Abdelpakey, Zhen-Hua Feng, Hyung Jin Chang, Ming Zhen, Matteo Dunnhofer, Xianxian Li, Yingjie Jiang, Luc Van Gool, Matej Kristan, Xiang Xu, Bastian Leibe, Xinyu Zhang, Filiz Gurkan, Jun Ha Lee, Yunhong Wang, Niki Martinel, Shang-Jhih Jhang, Yin Jun, Jianhua Li, Chengwei Zhang, Cheng Jiang, Muhammad Rana, Jie Ma, Houwen Peng, Gustav Häger, Zhiyong Feng, Wanli Xue, Gangshan Wu, Joni-Kristian Kamarainen, Zhibin Zhang, Alireza Memarmoghadam, Qili Deng, Daniel K. Du, Shiming Ge, Mohamed Shehata, Zhihong Fu, Chunhui Zhang, Yuzhen Niu, Xiaojun Wu, Rama Krishna Sai Subrahmanyam Gorthi, Hasan Saribas, Yuzhang Gu, Kenan Dai, Furao Shen, Qingjie Liu, Byeong Hak Kim, Hakan Cevikalp, Llukman Cerkezi, Jianbing Shen, Chenyan Wu, Alan Lukezic, Jiawen Zhu, Ziang Ma, Xiaohan Zhang, Limin Wang, Radu Timofte, Chi-Yi Tsai, Song Yan, Jonathon Luiten, Huchuan Lu, Kaihua Zhang, Tianyang Xu, Yutao Cui, Xiaolin Zhang
The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::717763c198da14f9ea29d111bbb1d71f
https://ora.ox.ac.uk/objects/uuid:d4585a6f-2205-4f68-b34a-8b6a61758cc8
https://ora.ox.ac.uk/objects/uuid:d4585a6f-2205-4f68-b34a-8b6a61758cc8
Publikováno v:
Multimedia Tools and Applications
Several recent person re-identification methods are focusing on learning discriminative representations by designing efficient metric learning loss functions. Other approaches design part based architectures to compute an informative descriptor based
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7cd4ff9a27e31c57ee0fe51e8ba5cdb
http://hdl.handle.net/11390/1222614
http://hdl.handle.net/11390/1222614
Publikováno v:
Image Analysis and Processing – ICIAP 2022 ISBN: 9783031064265
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::621cb8f17d51022d06ec7e5a1e4e4d59
https://doi.org/10.1007/978-3-031-06427-2_45
https://doi.org/10.1007/978-3-031-06427-2_45
Publikováno v:
Multimedia Tools and Applications. 79:32243-32258
With new architectures providing astonishing performance on many vision tasks, the interest in Convolutional Neural Networks (CNNs) has grown exponentially in the recent past. Such architectures, however, are not problem-free. For instance, one of th