Zobrazeno 1 - 10
of 95
pro vyhledávání: '"Matej, Kristan"'
Autor:
Valić, Damir1 (AUTHOR) dvalic@irb.hr, Mirković, Matej Kristan2 (AUTHOR) matej.k.mirkovic@gmail.com, Besendorfer, Višnja3 (AUTHOR) visnja.besendorfer@biol.pmf.unizg.hr, Teskeredžić, Emin4 (AUTHOR)
Publikováno v:
Fishes (MDPI AG). Jan2024, Vol. 9 Issue 1, p4. 12p.
Publikováno v:
Fishes, Vol 9, Iss 1, p 4 (2023)
Conservation of indigenous species, especially endemic ones, is of the utmost importance. Morphological determination of species is usually not sufficient; therefore, molecular phylogenetic analyses of the Illyrian chub, Squalius illyricus, and the Z
Externí odkaz:
https://doaj.org/article/f0dc97a1e94e4166b723864b05e62e76
Publikováno v:
Sensors, Vol 23, Iss 12, p 5386 (2023)
Maritime obstacle detection is critical for safe navigation of autonomous surface vehicles (ASVs). While the accuracy of image-based detection methods has advanced substantially, their computational and memory requirements prohibit deployment on embe
Externí odkaz:
https://doaj.org/article/b7eb7d1976104290a5737ed6ccd9c951
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Lojze Žust, Matej Kristan
Publikováno v:
Sensors, Vol 22, Iss 23, p 9139 (2022)
Robust maritime obstacle detection is critical for safe navigation of autonomous boats and timely collision avoidance. The current state-of-the-art is based on deep segmentation networks trained on large datasets. However, per-pixel ground truth labe
Externí odkaz:
https://doaj.org/article/0ff06e563cee4c2b924fcbff0a904dab
Publikováno v:
Geoscientific Model Development. 16:271-288
We propose a new deep-learning architecture HIDRA2 for sea level and storm tide modeling, which is extremely fast to train and apply and outperforms both our previous network design HIDRA1 and two state-of-the-art numerical ocean models (a NEMO engin
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 23:13403-13418
Small-sized unmanned surface vehicles (USV) are coastal water devices with a broad range of applications such as environmental control and surveillance. A crucial capability for autonomous operation is obstacle detection for timely reaction and colli
Autor:
Benjamin Kiefer, Matej Kristan, Janez Pers, Lojze Zust, Fabio Poiesi, Fabio Augusto De Alcantara Andrade, Alexandre Bernardino, Matthew Dawkins, Jenni Raitoharju, Yitong Quan, Adem Atmaca, Timon Hofer, Qiming Zhang, Yufei Xu, Jing Zhang, Dacheng Tao, Lars Sommer, Raphael Spraul, Hangyue Zhao, Hongpu Zhang, Yanyun Zhao, Jan Lukas Augustin, Eui-Ik Jeon, Impyeong Lee, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Sagar Verma, Siddharth Gupta, Shishir Muralidhara, Niharika Hegde, Daitao Xing, Nikolaos Evangeliou, Anthony Tzes, Vojtech Bartl, Jakub Spanhel, Adam Herout, Neelanjan Bhowmik, Toby P. Breckon, Shivanand Kundargi, Tejas Anvekar, Ramesh Ashok Tabib, Uma Mudengudi, Arpita Vats, Yang Song, Delong Liu, Yonglin Li, Shuman Li, Chenhao Tan, Long Lan, Vladimir Somers, Christophe De Vleeschouwer, Alexandre Alahi, Hsiang-Wei Huang, Cheng-Yen Yang, Jenq-Neng Hwang, Pyong-Kun Kim, Kwangju Kim, Kyoungoh Lee, Shuai Jiang, Haiwen Li, Zheng Ziqiang, Tuan-Anh Vu, Hai Nguyen-Truong, Sai-Kit Yeung, Zhuang Jia, Sophia Yang, Chih-Chung Hsu, Xiu-Yu Hou, Yu-An Jhang, Simon Yang, Mau-Tsuen Yang
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW).
We propose a new deep-learning architecture HIDRA2 for sea level and storm surge modeling, which is extremely fast to train and apply, and outperforms both our previous network design HIDRA1 and the state-of-the-art numerical ocean model (a NEMO engi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb8a0205390950f9dc4917523646dd54
https://doi.org/10.5194/egusphere-2022-618
https://doi.org/10.5194/egusphere-2022-618
Autor:
Matej Kristan, Lojze Žust
Publikováno v:
Sensors; Volume 22; Issue 23; Pages: 9139
Robust maritime obstacle detection is critical for safe navigation of autonomous boats and timely collision avoidance. The current state-of-the-art is based on deep segmentation networks trained on large datasets. However, per-pixel ground truth labe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fbb9b2ddcbefd17000c1c734d49c7c3
http://arxiv.org/abs/2206.13263
http://arxiv.org/abs/2206.13263