Výsledky vyhledávání - "Daniela, Giorgi"

Computational design, fabrication and evaluation of rubber protein models

Autor: Thomas Alderighi, Paolo Cignoni, Luigi Malomo, Daniela Giorgi, Monica Zoppè

Publikováno v: Computers & graphics 98 (2021): 177–187. doi:10.1016/j.cag.2021.05.010
info:cnr-pdr/source/autori:Alderighi T.; Giorgi D.; Malomo L.; Cignoni P.; Zoppè M./titolo:Computational design, fabrication and evaluation of rubber protein models/doi:10.1016%2Fj.cag.2021.05.010/rivista:Computers & graphics/anno:2021/pagina_da:177/pagina_a:187/intervallo_pagine:177–187/volume:98

Tangible 3D molecular models conceptualize complex phenomena in a stimulating and engaging format. This is especially true for learning environments, where additive manufacturing is increasingly used to produce teaching aids for chemical education. H

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bed166ea75fc70506812892ef423a6cb
https://doi.org/10.1016/j.cag.2021.05.010

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Cardio-metabolic risk modeling and assessment through sensor-based measurements

Autor: Daniela Giorgi, Luca Bastiani, Maria Aurora Morales, Maria Antonietta Pascali, Sara Colantonio, Giuseppe Coppini

Publikováno v: International Journal of Medical Informatics. 165:104823

Cardio-metabolic risk assessment in the general population is of paramount importance to reduce diseases burdened by high morbility and mortality. The present paper defines a strategy for out-of-hospital cardio-metabolic risk assessment, based on dat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f58247085870eb0bea46d14ee4b09e60
https://doi.org/10.1016/j.ijmedinf.2022.104823

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Optimizing Object Decomposition to Reduce Visual Artifacts in 3D Printing

Autor: Marco Callieri, Daniela Giorgi, Luigi Malomo, Irene Filoscia, Paolo Cignoni, Thomas Alderighi

Publikováno v: Computer Graphics Forum
Computer graphics forum
39 (2020): 423–434. doi:10.1111/cgf.13941
info:cnr-pdr/source/autori:Filoscia I.; Alderighi T.; Giorgi D.; Malomo L.; Callieri M.; Cignoni P./titolo:Optimizing object decomposition to reduce visual artifacts in 3D printing/doi:10.1111%2Fcgf.13941/rivista:Computer graphics forum (Print)/anno:2020/pagina_da:423/pagina_a:434/intervallo_pagine:423–434/volume:39

We propose a method for the automatic segmentation of 3D objects into parts which can be individually 3D printed and then reassembled by preserving the visual quality of the final object. Our technique focuses on minimizing the surface affected by su

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af284d8385948a3d347a95cb2781e2ca

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ReviewerNet: A visualization platform for the selection of academic reviewers

Autor: Mario Salinas, Federico Ponchio, Daniela Giorgi, Paolo Cignoni

Publikováno v: Computers & graphics 89 (2020): 77–87. doi:10.1016/j.cag.2020.04.006
info:cnr-pdr/source/autori:Salinas M.; Giorgi D.; Ponchio F.; Cignoni P./titolo:ReviewerNet: A visualization platform for the selection of academic reviewers/doi:10.1016%2Fj.cag.2020.04.006/rivista:Computers & graphics/anno:2020/pagina_da:77/pagina_a:87/intervallo_pagine:77–87/volume:89

We propose ReviewerNet, an online, interactive visualization system aimed to improve the reviewer selection process in the academic domain. Given a paper submitted for publication, we assume that good candidate reviewers can be chosen among the autho

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46041d57d10353b6d530e2e7adfbab67
https://openportal.isti.cnr.it/doc?id=people______::a7f97bb43ae1daa4f9dda3c62060bf10

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Elektronická kniha

Mathematical Tools for Shape Analysis and Description

Autor: Silvia Biasotti, Bianca Falcidieno, Daniela Giorgi, Michela Spagnuolo

This book is a guide for researchers and practitioners to the new frontiers of 3D shape analysis and the complex mathematical tools most methods rely on. The target reader includes students, researchers and professionals with an undergraduate mathema

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Towards a topological-geometrical theory of group equivariant non-expansive operators for data analysis and machine learning

Autor: Mattia G. Bergomi, Daniela Giorgi, Patrizio Frosini, Nicola Quercioli

Publikováno v: Nature Machine Intelligence 1 (2019): 423–433. doi:10.1038/s42256-019-0087-3
info:cnr-pdr/source/autori:Bergomi M.G.; Frosini P.; Giorgi D.; Quercioli N./titolo:Towards a topological-geometrical theory of group equivariant non-expansive operators for data analysis and machine learning/doi:10.1038%2Fs42256-019-0087-3/rivista:Nature Machine Intelligence/anno:2019/pagina_da:423/pagina_a:433/intervallo_pagine:423–433/volume:1

The aim of this paper is to provide a general mathematical framework for group equivariance in the machine learning context. The framework builds on a synergy between persistent homology and the theory of group actions. We define group-equivariant no

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3738d95944a9041a1777bf3094989f4
http://arxiv.org/abs/1812.11832

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Elektronická kniha

Computer Analysis of Images and Patterns : CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings

Autor: Mario Vento, Gennaro Percannella, Sara Colantonio, Daniela Giorgi, Bogdan J. Matuszewski, Hamideh Kerdegari, Manzoor Razaak

This book constitutes the refereed proceedings of two workshops held at the 18th International Conference on Computer Analysis of Images and Patterns, CAIP 2019, held in Salerno, Italy, in September 2019: First Workshop on Deep-learning based Compute

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Face morphology: Can it tell us something about body weight and fat?

Autor: Mariantonietta Pascali, Luca Bastiani, Bogdan J. Matuszewski, Maria Aurora Morales, Pedro Henriquez, E. Buzzigoli, Sara Colantonio, Daniela Giorgi

Publikováno v: Computers in biology and medicine 76 (2016): 238–249. doi:10.1016/j.compbiomed.2016.06.006
info:cnr-pdr/source/autori:Pascali M.A.; Giorgi D.; Bastiani L.; Buzzigoli E.; Henriquez P.; Matuszewski B.J.; Morales M.A.; Colantonio S./titolo:Face morphology: Can it tell us something about body weight and fat?/doi:10.1016%2Fj.compbiomed.2016.06.006/rivista:Computers in biology and medicine/anno:2016/pagina_da:238/pagina_a:249/intervallo_pagine:238–249/volume:76

This paper proposes a method for an automatic extraction of geometric features, related to weight parameters, from 3D facial data acquired with low-cost depth scanners. The novelty of the method relies both on the processing of the 3D facial data and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1ee21a7b508744bc40765bb554685e6
https://doi.org/10.1016/j.compbiomed.2016.06.006

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