Zobrazeno 1 - 10
of 217
pro vyhledávání: '"Popović Marija"'
Publikováno v:
Zaštita prirode, Vol 74, Iss 1, Pp 1-11 (2024)
An adequate land management is one of the greatest challenges in the field of environment. In this paper, the assessment of the intensity of soil erosion in the Lugomir river basin (central Serbia), which has an area of 451 km2, was investigated. The
Externí odkaz:
https://doaj.org/article/b67a0a8e35904581b4f00462d6b73258
Autor:
Rückin, Julius, Morilla-Cabello, David, Stachniss, Cyrill, Montijano, Eduardo, Popović, Marija
Robots are frequently tasked to gather relevant sensor data in unknown terrains. A key challenge for classical path planning algorithms used for autonomous information gathering is adaptively replanning paths online as the terrain is explored given l
Externí odkaz:
http://arxiv.org/abs/2410.17166
Robots need robust and flexible vision systems to perceive and reason about their environments beyond geometry. Most of such systems build upon deep learning approaches. As autonomous robots are commonly deployed in initially unknown environments, pr
Externí odkaz:
http://arxiv.org/abs/2410.10684
Autor:
Milanović Slobodan D., Popović Marija M., Dobrosavljević Jovan N., Kostić Igor M., Lazarević Jelica M.
Publikováno v:
Archives of Biological Sciences, Vol 72, Iss 1, Pp 63-69 (2020)
Gypsy moth, Lymantria dispar L. (Lepidoptera: Erebidae) feeds on a large number of tree species, while ash, Fraxinus spp. (Lamiales: Oleaceae) species are considered resistant and are only sporadically eaten. To assess the conditions under which late
Externí odkaz:
https://doaj.org/article/6335762b9bcf4faba67e4a8b5ccd019a
Adaptive informative path planning (AIPP) is important to many robotics applications, enabling mobile robots to efficiently collect useful data about initially unknown environments. In addition, learning-based methods are increasingly used in robotic
Externí odkaz:
http://arxiv.org/abs/2404.06940
Object reconstruction is relevant for many autonomous robotic tasks that require interaction with the environment. A key challenge in such scenarios is planning view configurations to collect informative measurements for reconstructing an initially u
Externí odkaz:
http://arxiv.org/abs/2403.16803
Many autonomous robotic applications require object-level understanding when deployed. Actively reconstructing objects of interest, i.e. objects with specific semantic meanings, is therefore relevant for a robot to perform downstream tasks in an init
Externí odkaz:
http://arxiv.org/abs/2403.11233
Autonomous robots are often employed for data collection due to their efficiency and low labour costs. A key task in robotic data acquisition is planning paths through an initially unknown environment to collect observations given platform-specific r
Externí odkaz:
http://arxiv.org/abs/2402.04894
Semantic segmentation enables robots to perceive and reason about their environments beyond geometry. Most of such systems build upon deep learning approaches. As autonomous robots are commonly deployed in initially unknown environments, pre-training
Externí odkaz:
http://arxiv.org/abs/2312.04402
Autor:
Radonjić Zorica, Jovanović-Srzentić Snežana, Pešić-Stevanović Ivana, Šerbić-Nonković Olivera, Popović Marija
Publikováno v:
Srpski Arhiv za Celokupno Lekarstvo, Vol 145, Iss 1-2, Pp 77-80 (2017)
Introduction. Jra is a high-frequency antigen belonging to the JR blood group system. Population studies have established that the Jr (a-) phenotype is rare. The clinical significance of anti-Jra antibodies is controversial. This case report describe
Externí odkaz:
https://doaj.org/article/0be84c765e6a40d089e436493a0f09a6