Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Tomyslav Sledevič"'
Publikováno v:
Agriculture, Vol 14, Iss 11, p 1890 (2024)
This paper addresses the challenge of accurately estimating bee orientations on beehive landing boards, which is crucial for optimizing beekeeping practices and enhancing agricultural productivity. The research utilizes YOLOv8 pose models, trained on
Externí odkaz:
https://doaj.org/article/342212e0b9a548aa97e72c78fe94ffd2
Autor:
Tomyslav Sledevič, Dalius Matuzevičius
Publikováno v:
Data in Brief, Vol 52, Iss , Pp 110060- (2024)
The datasets for bee detection, pose estimation and segmentation consist of organized folders containing both images and corresponding labels. The detection dataset comprises a total of 7200 individual frames collected at 8 different beehives. The po
Externí odkaz:
https://doaj.org/article/48e0a38fda3e4e3e9195df05fa050ba6
Publikováno v:
Applied Sciences, Vol 13, Iss 9, p 5604 (2023)
This paper discusses an algorithm that attempts to automatically calculate the effect of room reverberation by training a mathematical model based on a recurrent neural network on anechoic and reverberant sound samples. Modelling the room impulse res
Externí odkaz:
https://doaj.org/article/bae4c5a0291447608cc142dc4b23626d
Autor:
Mantas Tamulionis, Tomyslav Sledevič, Vytautas Abromavičius, Dovilė Kurpytė-Lipnickė, Dalius Navakauskas, Artūras Serackis, Dalius Matuzevičius
Publikováno v:
Applied Sciences, Vol 13, Iss 3, p 1264 (2023)
Taking smartphone-made videos for photogrammetry is a convenient approach because of the easy image collection process for the object being reconstructed. However, the video may contain a lot of relatively similar frames. Additionally, frames may be
Externí odkaz:
https://doaj.org/article/d0e17c561eb24d9cb01d9ce80f9d09c4
Publikováno v:
Agriculture, Vol 12, Iss 11, p 1849 (2022)
The condition of a bee colony can be predicted by monitoring bees upon hive entrance. The presence of pollen grains gives beekeepers significant information about the well-being of the bee colony in a non-invasive way. This paper presents a field-pro
Externí odkaz:
https://doaj.org/article/e8e0500c747f4c41b90f8971880d8326
Autor:
Tomas Jačionis, Vytautas Urbanavičius, Andrius Katkevičius, Vytautas Abromavičius, Artūras Serackis, Tomyslav Sledevič, Darius Plonis
Publikováno v:
Drones, Vol 6, Iss 10, p 306 (2022)
Artificial intelligence used in unmanned aerial vehicle (UAV) flight control systems tends to leave UAV control systems without any radio communication emissions, whose signatures in an electromagnetic spectrum (ES) are widely used to detect UAVs. Th
Externí odkaz:
https://doaj.org/article/a906ace13dd54013ae5f1b7583612145
Publikováno v:
2023 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::823625a8f65723a82f2cb56c04253799
https://doi.org/10.1109/estream59056.2023.10134852
https://doi.org/10.1109/estream59056.2023.10134852
Publikováno v:
2023 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3ad290256ebd44356aa000eedc0d4aa
https://doi.org/10.1109/estream59056.2023.10134800
https://doi.org/10.1109/estream59056.2023.10134800
Method of Singular Integral Equations for Analysis of Strip Structures and Experimental Confirmation
Publikováno v:
Mathematics, Vol 9, Iss 2, p 140 (2021)
This paper presents a rigorous solution of the Helmholtz equation for regular waveguide structures with the finite sizes of all cross-section elements that may have an arbitrary shape. The solution is based on the theory of Singular Integral Equation
Externí odkaz:
https://doaj.org/article/d241600089da40ae83cd44b9f32d1fa8
Building façade style classification from UAV imagery using a Pareto-optimized deep learning network
Autor:
Rytis Maskeliūnas, Andrius Katkevičius, Darius Plonis, Tomyslav Sledevič, Adas Meškėnas, Robertas Damaševičius
Publikováno v:
Electronics; Volume 11; Issue 21; Pages: 3450
The article focuses on utilizing unmanned aerial vehicles (UAV) to capture and classify building façades of various forms of cultural sites and structures. We propose a Pareto-optimized deep learning algorithm for building detection and classificati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1549eb6e809d9821eb38d1948c9c28f8
https://doi.org/10.3390/electronics11213450
https://doi.org/10.3390/electronics11213450
