Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Dimitrovski, Ivica"'
Accurate semantic segmentation of remote sensing imagery is critical for various Earth observation applications, such as land cover mapping, urban planning, and environmental monitoring. However, individual data sources often present limitations for
Externí odkaz:
http://arxiv.org/abs/2410.00469
The escalating use of Unmanned Aerial Vehicles (UAVs) as remote sensing platforms has garnered considerable attention, proving invaluable for ground object recognition. While satellite remote sensing images face limitations in resolution and weather
Externí odkaz:
http://arxiv.org/abs/2410.01092
Publikováno v:
IEEE Geoscience and Remote Sensing Letters (2024)
We investigate the utility of in-domain self-supervised pre-training of vision models in the analysis of remote sensing imagery. Self-supervised learning (SSL) has emerged as a promising approach for remote sensing image classification due to its abi
Externí odkaz:
http://arxiv.org/abs/2307.01645
The volume contains selected contributions from the Machine Learning Challenge "Discover the Mysteries of the Maya", presented at the Discovery Challenge Track of The European Conference on Machine Learning and Principles and Practice of Knowledge Di
Externí odkaz:
http://arxiv.org/abs/2208.03163
We present AiTLAS: Benchmark Arena -- an open-source benchmark suite for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO). To this end, we present a comprehensive comparative analysis of more tha
Externí odkaz:
http://arxiv.org/abs/2207.07189
The AiTLAS toolbox (Artificial Intelligence Toolbox for Earth Observation) includes state-of-the-art machine learning methods for exploratory and predictive analysis of satellite imagery as well as repository of AI-ready Earth Observation (EO) datase
Externí odkaz:
http://arxiv.org/abs/2201.08789
Autor:
Dimitrovski, Ivica1 (AUTHOR) ivica.dimitrovski@finki.ukim.mk, Spasev, Vlatko1 (AUTHOR), Loshkovska, Suzana1 (AUTHOR), Kitanovski, Ivan1 (AUTHOR)
Publikováno v:
Remote Sensing. Jun2024, Vol. 16 Issue 12, p2077. 24p.
Publikováno v:
In Acta Astronautica September 2023 210:411-427
Traditional recommendation systems rely on past usage data in order to generate new recommendations. Those approaches fail to generate sensible recommendations for new users and items into the system due to missing information about their past intera
Externí odkaz:
http://arxiv.org/abs/1706.05730
Autor:
Dimitrovski, Ivica1,2 (AUTHOR), Kitanovski, Ivan1,2 (AUTHOR), Panov, Panče1,3 (AUTHOR), Kostovska, Ana1,3 (AUTHOR), Simidjievski, Nikola1,3,4 (AUTHOR), Kocev, Dragi1,3 (AUTHOR) dragi@bvlabs.ai
Publikováno v:
Remote Sensing. May2023, Vol. 15 Issue 9, p2343. 48p.