Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Nikola S. Mirkov"'
Autor:
Dušan P. Nikezić, Dušan S. Radivojević, Nikola S. Mirkov, Ivan M. Lazović, Tatjana A. Miljojčić
Publikováno v:
Symmetry, Vol 16, Iss 5, p 525 (2024)
In this study, the idea of using a fully symmetric U-Net deep learning model for forecasting a segmented image of high global aerosol concentrations is implemented. As the forecast relies on historical data, the model used a sequence of the last eigh
Externí odkaz:
https://doaj.org/article/9f9ba16553c942a0bb1b149d256ce50a
Publikováno v:
Mathematics, Vol 12, Iss 6, p 826 (2024)
In order to better predict the high aerosol concentrations associated with air pollution and climate change, a machine learning model was developed using transfer learning and the segmentation process of global satellite images. The main concept of t
Externí odkaz:
https://doaj.org/article/ea4a7afdb00b4e42affb6fd6f749ddeb
Autor:
Nikola S. Mirkov, Dušan S. Radivojević, Ivan M. Lazović, Uzahir R. Ramadani, Dušan P. Nikezić
Publikováno v:
Vojnotehnički Glasnik, Vol 71, Iss 1, Pp 66-83 (2023)
Introduction/purpose: The paper presents a new state-of-the-art method that involves NASA satellite imagery with the latest deep learning model for a spatiotemporal sequence forecasting problem. Satellite-retrieved aerosol information is very usef
Externí odkaz:
https://doaj.org/article/8f93b03bd288458393038b868a407009
Autor:
Dušan S. Radivojević, Ivan M. Lazović, Nikola S. Mirkov, Uzahir R. Ramadani, Dušan P. Nikezić
Publikováno v:
Mathematics, Vol 11, Iss 7, p 1744 (2023)
The attention mechanism in natural language processing and self-attention mechanism in vision transformers improved many deep learning models. An implementation of the self-attention mechanism with the previously developed ConvLSTM sequence-to-one mo
Externí odkaz:
https://doaj.org/article/ccd826a2679146b883ca4f256aee89d9
Autor:
Dušan P. Nikezić, Uzahir R. Ramadani, Dušan S. Radivojević, Ivan M. Lazović, Nikola S. Mirkov
Publikováno v:
Mathematics, Vol 10, Iss 18, p 3392 (2022)
Mathematical methods are the basis of most models that describe the natural phenomena around us. However, the well-known conventional mathematical models for atmospheric modeling have some limitations. Machine learning with Big Data is also based on
Externí odkaz:
https://doaj.org/article/0dab65a01d414374af0e2a28fb9067d6