Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Luka Čehovin Zajc"'
Publikováno v:
Remote Sensing, Vol 16, Iss 2, p 270 (2024)
Crop classification is an important task in remote sensing with many applications, such as estimating yields, detecting crop diseases and pests, and ensuring food security. In this study, we combined knowledge from remote sensing, machine learning, a
Externí odkaz:
https://doaj.org/article/4f7598a1aa704e23b30998039b431564
Autor:
Luka Čehovin Zajc
Publikováno v:
SoftwareX, Vol 12, Iss , Pp 100623- (2020)
We present a modular software package for conducting single-target visual object tracking experiments and analyzing results. Our software supports many of the common usage patterns in visual tracking evaluation out of the box, but is also modular and
Externí odkaz:
https://doaj.org/article/91b50ba353764c568e41d9d245ee0123
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:
European Journal of Management and Business Economics
Purpose The purpose of this paper is to evaluate innovations in intellectual property rights (IPR) databases, techniques and software tools, with an emphasis on selected new developments and their contribution towards achieving advantages for IPR man
Publikováno v:
IEEE transactions on cybernetics. 51(12)
A long-term visual object tracking performance evaluation methodology and a benchmark are proposed. Performance measures are designed by following a long-term tracking definition to maximize the analysis probing strength. The new measures outperform
Autor:
Shohreh Kasaei, Shaochuan Zhao, Zhen-Hua Feng, Shuhao Chen, Xiaojun Wu, Rama Krishna Sai Subrahmanyam Gorthi, Jianlong Fu, Gustavo Fernandez, Wei Lu, Roman Pflugfelder, Haibin Ling, Yuzhang Gu, Kenan Dai, Hui Li, Martin Danelljan, Felix Järemo Lawin, Jiaqian Yu, Xiaoyun Yang, Yingming Wang, Jinyu Yang, Yuncon Yao, Gian Luca Foresti, Bedirhan Uzun, Xue-Feng Zhu, Heng Fan, Haoran Bai, Houqiang Li, Alexander G. Hauptmann, Thomas B. Schön, Guangqi Chen, Mohana Murali Dasari, Ziang Ma, Pengyu Zhang, Joni-Kristian Kamarainen, Dong Wang, Yunsung Lee, Fei Wang, Fredrik K. Gustafsson, Bin Yan, Ondrej Drbohlav, Song Yan, Fei Xie, Linyuan Wang, Michael Felsberg, Alan Lukežič, Christian Micheloni, Wengang Zhou, Yingjie Jiang, Kaicheng Yu, Chen Qian, Yu Ye, Haojie Zhao, Seyed Mojtaba Marvasti-Zadeh, Huchuan Lu, Bing Li, Jingtao Xu, Jesús Bescós, Matej Kristan, Tianyang Xu, Yushan Zhang, Hasan Saribas, Linbo He, Xiaolin Zhang, Kaiwen Liu, Jun Yin, Lijun Wang, Hakan Cevikalp, Alireza Memarmoghadam, Seokeon Choi, Alvaro Garcia-Martin, Awet Haileslassie Gebrehiwot, Zezhou Wang, Junhyun Lee, Ning Wang, Luca Bertinetto, Hari Chandana Kuchibhotla, Javad Khaghani, Anton Varfolomieiev, Luc Van Gool, Jiří Matas, Josef Kittler, Kang Yang, Xi Qiu, Philip H. S. Torr, Haitao Zhang, Xiao Ke, Ales Leonardis, Weiming Hu, Radu Timofte, Chi-Yi Tsai, Shoumeng Qiu, Zhipeng Zhang, Hossein Ghanei-Yakhdan, Houwen Peng, Luka Čehovin Zajc, Qiang Wang, Andreas Robinson, Matteo Dunnhofer, Yiwei Chen, Zhirong Wu, Jianhua Li, Miao Cheng, Yuezhou Li, Goutam Bhat, Zhijun Mai, Zhangyong Tang, Li Zhang, Li Cheng
Publikováno v:
Computer Vision – ECCV 2020 Workshops ISBN: 9783030682378
ECCV Workshops (5)
ECCV Workshops (5)
The Visual Object Tracking challenge VOT2020 is the eighth annual tracker benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::722c41ae8bc63845cb1731bcc91fd851
http://hdl.handle.net/11390/1205562
http://hdl.handle.net/11390/1205562
Publikováno v:
International Journal of Computer Vision. 126:671-688
Short-term tracking is an open and challenging problem for which discriminative correlation filters (DCF) have shown excellent performance. We introduce the channel and spatial reliability concepts to DCF tracking and provide a learning algorithm for
Autor:
Houqiang Li, Huchuan Lu, Siwen Wang, Rafael Martin-Nieto, Efstratios Gavves, Feng Li, Manqiang Che, Erhan Gundogdu, Priya Mariam Raju, Xiaofan Zhang, Roman Pflugfelder, Yan Lu, Xinmei Tian, Martin Danelljan, Deepak Mishra, Guilherme Sousa Bastos, Honggang Zhang, Heng Fan, Mohamed H. Abdelpakey, Zhen-Hua Feng, Wang Wei, Andrej Muhič, Wengang Zhou, Deming Chen, Haojie Zhao, Sihang Wu, Richard M. Everson, Junfei Zhuang, Qin Zhou, Myunggu Kang, Abel Gonzalez-Garcia, Pablo Vicente-Moñivar, Richard Bowden, Horst Possegger, Yicai Yang, Andrea Vedaldi, Jaime Spencer Martin, Jongwon Choi, Yunhua Zhang, Yiannis Demiris, Seokeon Choi, Alireza Memarmoghadam, Wangmeng Zuo, Changzhen Xiong, Yuxuan Sun, Daijin Kim, Yuhong Li, Qing Guo, Tang Ming, Arnold W. M. Smeulders, Hamed Kiani Galoogahi, Zhihui Wang, Asanka G. Perera, Fahad Shahbaz Khan, George De Ath, Shuangping Huang, Qian Ruihe, Philip H. S. Torr, Haojie Li, Zhiqun He, João F. Henriques, Namhoon Lee, Chong Sun, Jorge Rodríguez Herranz, Vincenzo Santopietro, Lijun Wang, Qiang Wang, Gustavo Fernandez, Shuai Bai, Weiming Hu, Ondrej Miksik, Dongyoon Wee, Xiaohe Wu, Goutam Bhat, Yifan Jiao, A. Aydin Alatan, Alfredo Petrosino, Ran Tao, Tianyang Xu, Sergio Vivas, Cheng Tian, Yee Wei Law, Wei Feng, José M. Martínez, Luca Bertinetto, Runling Wang, Liu Si, Tianzhu Zhang, Tomas Vojir, Mario Edoardo Maresca, Lichao Zhang, Changick Kim, Luka Čehovin Zajc, Lingxiao Yang, Yan Li, Javaan Chahl, Simon Hadfield, Chong Luo, Jiří Matas, Ales Leonardis, Jack Valmadre, Pedro Senna, Josef Kittler, Klemen Grm, Cong Hao, Haibin Ling, Isabela Drummond, Zheng Zhang, Fan Yang, Joakim Johnander, Tobias Fischer, Gorthi R. K. Sai Subrahmanyam, Jinyoung Sung, Jin-Young Choi, Bo Li, Hui Zhi, Álvaro Iglesias-Arias, Joost van de Weijer, Hyung Jin Chang, Jinqing Qi, Michael Felsberg, Francesco Battistone, Sangdoo Yun, Wei Zou, Huiyun Li, Boyu Chen, Zheng Zhu, Jing Li, Abdelrahman Eldesokey, Litu Rout, Matej Kristan, Mohamed Shehata, Fei Zhao, Changsheng Xu, Alan Lukežič, Yi Wu, Wenjun Zeng, Lutao Chu, Vitomir Struc, Stuart Golodetz, Alvaro Garcia-Martin, Dong Wang, Junyu Gao, Hankyeol Lee, Hyemin Lee, Ning Wang, Wei Wu, Anfeng He, Xiaojun Wu, Rama Krishna Sai Subrahmanyam Gorthi, Payman Moallem, Peixia Li, Jinqiao Wang, Erik Velasco-Salido, Ming-Hsuan Yang
Publikováno v:
European Conference on Computer Vision
Lecture Notes in Computer Science ISBN: 9783030110086
ECCV Workshops (1)
Lecture Notes in Computer Science ISBN: 9783030110086
ECCV Workshops (1)
The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision confe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a449874fbb7a60c1bc50564cd356140f
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-161343
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-161343
Publikováno v:
Computer Vision – ACCV 2018 ISBN: 9783030208899
ACCV (2)
ACCV (2)
We propose FuCoLoT – a Fully Correlational Long-term Tracker. It exploits the novel DCF constrained filter learning method to design a detector that is able to re-detect the target in the whole image efficiently. FuCoLoT maintains several correlati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c74c633092ab78ef8ecf0b1cbd4c6c71
https://doi.org/10.1007/978-3-030-20890-5_38
https://doi.org/10.1007/978-3-030-20890-5_38
Publikováno v:
Robotics in Education ISBN: 9783319970844
RiE
RiE
In this paper we present and evaluate the usage of an open-source robotic manipulator platform, that we have developed, in the context of various educational scenarios that we have conducted. The system was tested in multiple diverse learning scenari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::079e0b58cea49ba914167fd4684bd2b7
https://doi.org/10.1007/978-3-319-97085-1_19
https://doi.org/10.1007/978-3-319-97085-1_19