Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Pers, Janez"'
The progress in maritime obstacle detection is hindered by the lack of a diverse dataset that adequately captures the complexity of general maritime environments. We present the first maritime panoptic obstacle detection benchmark LaRS, featuring sce
Externí odkaz:
http://arxiv.org/abs/2308.09618
Artificial intelligence applications enable farmers to optimize crop growth and production while reducing costs and environmental impact. Computer vision-based algorithms in particular, are commonly used for fruit segmentation, enabling in-depth anal
Externí odkaz:
http://arxiv.org/abs/2307.01064
Autor:
Kiefer, Benjamin, Kristan, Matej, Perš, Janez, Žust, Lojze, Poiesi, Fabio, Andrade, Fabio Augusto de Alcantara, Bernardino, Alexandre, Dawkins, Matthew, Raitoharju, Jenni, Quan, Yitong, Atmaca, Adem, Höfer, Timon, Zhang, Qiming, Xu, Yufei, Zhang, Jing, Tao, Dacheng, Sommer, Lars, Spraul, Raphael, Zhao, Hangyue, Zhang, Hongpu, Zhao, Yanyun, Augustin, Jan Lukas, Jeon, Eui-ik, Lee, Impyeong, Zedda, Luca, Loddo, Andrea, Di Ruberto, Cecilia, Verma, Sagar, Gupta, Siddharth, Muralidhara, Shishir, Hegde, Niharika, Xing, Daitao, Evangeliou, Nikolaos, Tzes, Anthony, Bartl, Vojtěch, Špaňhel, Jakub, Herout, Adam, Bhowmik, Neelanjan, Breckon, Toby P., Kundargi, Shivanand, Anvekar, Tejas, Desai, Chaitra, Tabib, Ramesh Ashok, Mudengudi, Uma, Vats, Arpita, Song, Yang, Liu, Delong, Li, Yonglin, Li, Shuman, Tan, Chenhao, Lan, Long, Somers, Vladimir, De Vleeschouwer, Christophe, Alahi, Alexandre, Huang, Hsiang-Wei, Yang, Cheng-Yen, Hwang, Jenq-Neng, Kim, Pyong-Kun, Kim, Kwangju, Lee, Kyoungoh, Jiang, Shuai, Li, Haiwen, Ziqiang, Zheng, Vu, Tuan-Anh, Nguyen-Truong, Hai, Yeung, Sai-Kit, Jia, Zhuang, Yang, Sophia, Hsu, Chih-Chung, Hou, Xiu-Yu, Jhang, Yu-An, Yang, Simon, Yang, Mau-Tsuen
The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritim
Externí odkaz:
http://arxiv.org/abs/2211.13508
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
Externí odkaz:
http://arxiv.org/abs/2105.02359
Autor:
Koporec, Gregor, Perš, Janez
Segmentation is generally an ill-posed problem since it results in multiple solutions and is, therefore, hard to define ground truth data to evaluate algorithms. The problem can be naively surpassed by using only one annotator per image, but such acq
Externí odkaz:
http://arxiv.org/abs/2007.11361
Autor:
Muhovič, Jon, Perš, Janez
We address the problem of optical decalibration in mobile stereo camera setups, especially in context of autonomous vehicles. In real world conditions, an optical system is subject to various sources of anticipated and unanticipated mechanical stress
Externí odkaz:
http://arxiv.org/abs/2001.05267
Autor:
Koporec, Gregor, Perš, Janez
Publikováno v:
In Pattern Recognition June 2023 138
A new obstacle detection algorithm for unmanned surface vehicles (USVs) is presented. A state-of-the-art graphical model for semantic segmentation is extended to incorporate boat pitch and roll measurements from the on-board inertial measurement unit
Externí odkaz:
http://arxiv.org/abs/1802.07956
Obstacle detection plays an important role in unmanned surface vehicles (USV). The USVs operate in highly diverse environments in which an obstacle may be a floating piece of wood, a scuba diver, a pier, or a part of a shoreline, which presents a sig
Externí odkaz:
http://arxiv.org/abs/1503.01918
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.