Výsledky vyhledávání - "Illya Bakurov"

Akademický článek

General Purpose Optimization Library (GPOL): A Flexible and Efficient Multi-Purpose Optimization Library in Python

Autor: Illya Bakurov, Marco Buzzelli, Mauro Castelli, Leonardo Vanneschi, Raimondo Schettini

Publikováno v: Applied Sciences, Vol 11, Iss 11, p 4774 (2021)

Several interesting libraries for optimization have been proposed. Some focus on individual optimization algorithms, or limited sets of them, and others focus on limited sets of problems. Frequently, the implementation of one of them does not precise

Externí odkaz: https://doaj.org/article/7f260f80bb0a4140af084bf379342ac1

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Full-Reference Image Quality Expression via Genetic Programming

Autor: Illya Bakurov, Marco Buzzelli, Raimondo Schettini, Mauro Castelli, Leonardo Vanneschi

Bakurov, I., Buzzelli, M., Schettini, R., Castelli, M., & Vanneschi, L. (2023). Full-Reference Image Quality Expression via Genetic Programming. IEEE Transactions on Image Processing, 32, 1458-1473. https://doi.org/10.1109/TIP.2023.3244662--- This wo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c6b05ca6d1d8e5e0027e69cbcb51ac7f
https://hdl.handle.net/10362/149941

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Genetic programming for structural similarity design at multiple spatial scales

Autor: Illya Bakurov, Marco Buzzelli, Mauro Castelli, Raimondo Schettini, Leonardo Vanneschi

Bakurov, I., Buzzelli, M., Castelli, M., Schettini, R., & Vanneschi, L. (2022). Genetic programming for structural similarity design at multiple spatial scales. In GECCO ’22. Proceedings of the 2022 Genetic and Evolutionary Computation Conference (

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb0b7d53a1c26bc8d57c7de16ff9a0dc
https://hdl.handle.net/10362/141872

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Parameters optimization of the Structural Similarity Index

Autor: Raimondo Schettini, Leonardo Vanneschi, Illya Bakurov, Mauro Castelli, Marco Buzzelli

Publikováno v: London Imaging Meeting. 1:19-23

Bakurov, I., Buzzelli, M., Castelli, M., Schettini, R., & Vanneschi, L. (2020). Parameters optimization of the Structural Similarity Index. In London Imaging Meeting 2020: Future Colour Imaging (1 ed., Vol. 2020, pp. 19-23). (London Imaging Meeting).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3405b5941546eab808b5f24c689c27f
https://doi.org/10.2352/issn.2694-118x.2020.lim-13

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A data-driven approach

Autor: Raimondo Schettini, Marco Buzzelli, Mauro Castelli, Leonardo Vanneschi, Illya Bakurov

Publikováno v: Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP

Bakurov, I., Buzzelli, M., Schettini, R., Castelli, M., & Vanneschi, L. (2022). Structural similarity index (SSIM) revisited: A data-driven approach. Expert Systems with Applications, 189, 1-19. [116087]. [Advanced online publication on 27 October 20

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9843548d4dbccae8705fb8a2d19cdea0

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Genetic programming for stacked generalization

Autor: Olivier Gau, Mauro Castelli, Francesco Fontanella, Illya Bakurov, Leonardo Vanneschi

Publikováno v: Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP

Bakurov, I., Castelli, M., Gau, O., Fontanella, F., & Vanneschi, L. (2021). Genetic programming for stacked generalization. Swarm and Evolutionary Computation, 65, 1-14. [100913]. https://doi.org/10.1016/j.swevo.2021.100913 In machine learning, ensem

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A Greedy Iterative Layered Framework for Training Feed Forward Neural Networks

Autor: Mauro Castelli, Leonardo Vanneschi, Illya Bakurov, C. L. Tecce, Leonardo Lucio Custode, A. Della Cioppa

Publikováno v: Applications of Evolutionary Computation ISBN: 9783030437213
EvoApplications

Custode, L. L., Tecce, C. L., Bakurov, I., Castelli, M., Cioppa, A. D., & Vanneschi, L. (2020). A Greedy Iterative Layered Framework for Training Feed Forward Neural Networks. In P. A. Castillo, J. L. Jiménez Laredo, & F. Fernández de Vega (Eds.),

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fdd87b4788cb24353ae1fec122d62bb
http://hdl.handle.net/11386/4781248

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Towards the use of vector based GP to predict physiological time series

Autor: Illya Bakurov, Sara Silva, Irene Azzali, Leonardo Vanneschi, Mario Giacobini, Marco Ivaldi

Publikováno v: Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP

Azzali, I., Vanneschi, L., Bakurov, I., Silva, S., Ivaldi, M., & Giacobini, M. (2020). Towards the use of vector based GP to predict physiological time series. Applied Soft Computing Journal, 89(April), [106097]. https://doi.org/10.1016/j.asoc.2020.1

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f59f939a56aae6405e68fe8a358ecbf
http://hdl.handle.net/2318/1725690

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Supporting medical decisions for treating rare diseases through genetic programming

Autor: Illya Bakurov, Mauro Castelli, Maria João Freitas, Leonardo Vanneschi

Publikováno v: Applications of Evolutionary Computation ISBN: 9783030166915
EvoApplications

Bakurov, I., Castelli, M., Vanneschi, L., & Freitas, M. J. (2019). Supporting medical decisions for treating rare diseases through genetic programming. In P. Kaufmann, & P. A. Castillo (Eds.), Applications of Evolutionary Computation: 22nd Internatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03b1a19d7296116316708ce75e805dd1
https://hdl.handle.net/10362/91519

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Evolving PSO algorithm design in vector fields using geometric semantic GP

Autor: Leonardo Vanneschi, Illya Bakurov, Sanaz Mostaghim, Palina Bartashevich

Publikováno v: GECCO (Companion)

Bartashevich, P., Mostaghim, S., Bakurov, I., & Vanneschi, L. (2018). Evolving PSO algorithm design in vector fields using geometric semantic GP. In GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Compan

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::472d96a58e20353fb62f70ebdca85521
https://doi.org/10.1145/3205651.3205760

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