Zobrazeno 1 - 10 of 203 pro vyhledávání: '"S. Biasotti"'
1
Akademický článek
A COMPARISON OF METHODS FOR THE APPROXIMATION AND ANALYSIS OF RAINFALL FIELDS IN ENVIRONMENTAL APPLICATIONS
Autor: G. Patané, A. Cerri, V. Skytt, S. Pittaluga, S. Biasotti, D. Sobrero, T. Dokken, M. Spagnuolo
Publikováno v: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol II-3-W5, Pp 523-530 (2015)
Digital environmental data are becoming commonplace and the amount of information they provide is huge, yet complex to process, due to the size, variety, and dynamic nature of the data captured by the available sensing devices. Making use of the data
Externí odkaz: https://doaj.org/article/a2192e074c0242149ee31a5443e82530
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3
Akademický článek
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4
Akademický článek
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5
Akademický článek
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6
Hough Transform for Detecting Space Curves in Digital 3D Models
Autor: C. Romanengo, S. Biasotti, B. Falcidieno
Publikováno v: Journal of mathematical imaging and vision (Dordr., Online) (2022). doi:10.1007/s10851-021-01066-8
info:cnr-pdr/source/autori:C. Romanengo, S. Biasotti and B. Falcidieno/titolo:Hough Transform for Detecting Space Curves in Digital 3D Models/doi:10.1007%2Fs10851-021-01066-8/rivista:Journal of mathematical imaging and vision (Dordr., Online)/anno:2022/pagina_da:/pagina_a:/intervallo_pagine:/volume
We present and analyse the Hough transform (HT) to recognise and approximate space curves in digital models, a problem that is not currently addressed by the standard HT. Our method works on meshes and point clouds and applies to models even incomple
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=cnr_________::42575ceb3bd932901a13bc818c8f405a
https://link.springer.com/article/10.1007%2Fs10851-021-01066-8
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7
The role of mesh quality and mesh quality indicators in the virtual element method
Autor: T. Sorgente, S. Biasotti, G. Manzini, M. Spagnuolo
Publikováno v: Advances in computational mathematics 48 (2022). doi:10.1007/s10444-021-09913-3
info:cnr-pdr/source/autori:T. Sorgente, s. Biasotti, G. Manzini and M. Spagnuolo/titolo:The role of mesh quality and mesh quality indicators in the virtual element method/doi:10.1007%2Fs10444-021-09913-3/rivista:Advances in computational mathematics/anno:2022/pagina_da:/pagina_a:/intervallo_pagine:/volume:48
Since its introduction, the Virtual Element Method (VEM) was shown to be able to deal with a large variety of polygons, while achieving good convergence rates. The regularity assumptions proposed in the VEM literature to guarantee the convergence on
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fac8de01add054463f53ac374f71a2e8
https://doi.org/10.1007/s10444-021-09913-3
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8
Foreword to the special issue on 3D object retrieval 2021 workshop (3DOR2021)
Autor: S. Biasotti, R.M. Dyke, Y.-K. Lai, P.L. Rosin, R.Veltkamp
Publikováno v: info:cnr-pdr/source/autori:S. Biasotti, R.M. Dyke, Y.-K. Lai,P.L. Rosin and R.Veltkamp/titolo:Foreword to the special issue on 3D object retrieval 2021 workshop (3DOR2021)/editore:/anno:2021
N/A
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=cnr_________::66369d7476132d0f57fa76e50b87736e
https://publications.cnr.it/doc/458558
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9
Automatic Segmentation of Archaeological Fragments with Relief Patterns using Convolutional Neural Networks
Autor: E. Moscoso Thompson, A. Ranieri, S. Biasotti
Publikováno v: EUROGRAPHICS Workshop on Graphics and Cultural Heritage (2021), pp. 93–102, Bournemouth, UK, November 4-6, 2021
info:cnr-pdr/source/autori:E. Moscoso Thompson, A. Ranieri, S. Biasotti/congresso_nome:EUROGRAPHICS Workshop on Graphics and Cultural Heritage (2021)/congresso_luogo:Bournemouth, UK/congresso_data:November 4-6, 2021/anno:2021/pagina_da:93/pagina_a:102/intervallo_pagine:93–102
The recent commodification of high-quality 3D scanners is leading to the possibility of capturing models of archaeological finds and automatically recognizing their surface reliefs. We present our advancements in this field using Convolutional Neural
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b637f31d6314bb0fde9f6b0e67f1959
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10
Foreword to the Special Section on Smart Tool and Applications for Graphics (STAG 2020)
Autor: R. Pintus, S. Biasotti, S.Berretti
Publikováno v: info:cnr-pdr/source/autori:R. Pintus, S. Biasotti and S.Berretti/titolo:Foreword to the Special Section on Smart Tool and Applications for Graphics (STAG 2020)/editore:/anno:2021
This special issue contains extended and revised versions of the best papers presented at the 7th Conference on Smart Tools and Applications in Graphics (STAG 2020), held virtually on November 12-13, 2020. The two selected papers cover two different
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=cnr_________::6f82b7c4d91a9f9851569df2e1bd6f29
https://publications.cnr.it/doc/458552
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