SPAGNUOLO, MICHELA
SPAGNUOLO, MICHELA
Istituto di Matematica Applicata e Tecnologie Informatiche - IMATI -
A survey of indicators for mesh quality assessment
2023 T. Sorgente; S. Biasotti; G. Manzini;M. Spagnuolo
Correction: Mesh quality agglomeration algorithm for the virtual element method applied to discrete fracture networks
2023 Sorgente, T; Vicini, F; S Biasotti, S Berrone; Manzini, G; Spagnuolo, M
Mesh quality agglomeration algorithm for the virtual element method applied to discrete fracture networks
2023 T. Sorgente; F. Vicini; S. Berrone; S. Biasotti; G. Manzini;M. Spagnuolo
Polyhedral mesh quality indicator for the Virtual Element Method
2022 Sorgente, T; Biasotti, S; Manzini, G; Spagnuolo, M
Polyhedron kernel computation using a geometric approach
2022 Sorgente, T; Biasotti, S; Spagnuolo, M
Potential of the geometric layer in urban digital twins
2022 Scalas, Andreas; Scalas, Andreas; Cabiddu, Daniela; Cabiddu, Daniela; Mortara, Michela; Mortara, Michela; Spagnuolo, Michela; Mortara, Michela
The role of mesh quality and mesh quality indicators in the virtual element method
2022 Sorgente, T; Biasotti, S; Manzini, G; Spagnuolo, M
Benchmarking the geometrical robustness of a Virtual Element Poisson solver
2021 Mattene, ; Biasotti, S; Bertoluzza, S; Cabiddu, D; Livesu, M; Patanè, G; Pennacchio, M; Prada, D; Spagnuolo, M
Analysis of 3D segmented anatomical districts through grey-levels mapping
2020 M. Paccini; G. Patane; M. Spagnuolo
Representing quantitative documentation of 3D cultural heritage artefacts with CIDOC CRMdig
2020 C.E. Catalano; V. Vassallo; S. Hermon; M. Spagnuolo
Sea Monitoring Made Simple and Efficient
2020 S. Berretta; D. Cabiddu; M. Mortara;M. Spagnuolo
A pipeline for the preparation of artefacts that provides annotations persistence
2019 Scalas, A; Mortara, M; Spagnuolo, M
Context-adaptive navigation of 3D model collections
2019 Biasotti, S; MOSCOSO THOMPSON, Elia; Spagnuolo, M
Foreword to the special section on Eurographics workshop on 3D object retrieval 2017
2018 Lavoue, G; Pratikakis, I; Dupont, F; Ovsjanikov, M; Spagnuolo, M
Supporting shared hypothesis testing in the biomedical domain.
2018 A. Agibetov; E. JimenezRuiz; M. Ondresik; A. Solimando; I. Banerjee; G. Guerrini; C.E. Catalano; J.M. Oliveira; G. Patane; R.L Reis;M. Spagnuolo
Topology-driven shape chartification
2018 Tsorgente, ; Biasotti, S; Livesu, M; Spagnuolo, M
Combination of visual and symbolic knowledge: A survey in anatomy
2017 I. Banerjee; G. Patané;M. Spagnuolo
Comparing methods for the approximation of rainfall fields in environmental applications
2017 Patané, G; Cerri, A; Skytt, V; Pittaluga, S; Biasotti, S; Sobrero, D; Dokken, T; Spagnuolo, M
Explicit cylindrical maps for general tubular shapes
2017 Livesu, M; Attene, M; Patané, G; Spagnuolo, M
3D skeletons: a state-of-the-art report
2016 Tagliasacchi, A; Delame, T; Spagnuolo, M; Amenta, N; Telea, A
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| A survey of indicators for mesh quality assessment | 1-gen-2023 | T. Sorgente; S. Biasotti; G. Manzini;M. Spagnuolo | |
| Correction: Mesh quality agglomeration algorithm for the virtual element method applied to discrete fracture networks | 1-gen-2023 | Sorgente, T; Vicini, F; S Biasotti, S Berrone; Manzini, G; Spagnuolo, M | |
| Mesh quality agglomeration algorithm for the virtual element method applied to discrete fracture networks | 1-gen-2023 | T. Sorgente; F. Vicini; S. Berrone; S. Biasotti; G. Manzini;M. Spagnuolo | |
| Polyhedral mesh quality indicator for the Virtual Element Method | 1-gen-2022 | Sorgente, T; Biasotti, S; Manzini, G; Spagnuolo, M | |
| Polyhedron kernel computation using a geometric approach | 1-gen-2022 | Sorgente, T; Biasotti, S; Spagnuolo, M | |
| Potential of the geometric layer in urban digital twins | 1-gen-2022 | Scalas, Andreas; Scalas, Andreas; Cabiddu, Daniela; Cabiddu, Daniela; Mortara, Michela; Mortara, Michela; Spagnuolo, Michela; Mortara, Michela | |
| The role of mesh quality and mesh quality indicators in the virtual element method | 1-gen-2022 | Sorgente, T; Biasotti, S; Manzini, G; Spagnuolo, M | |
| Benchmarking the geometrical robustness of a Virtual Element Poisson solver | 1-gen-2021 | Mattene, ; Biasotti, S; Bertoluzza, S; Cabiddu, D; Livesu, M; Patanè, G; Pennacchio, M; Prada, D; Spagnuolo, M | |
| Analysis of 3D segmented anatomical districts through grey-levels mapping | 1-gen-2020 | M. Paccini; G. Patane; M. Spagnuolo | |
| Representing quantitative documentation of 3D cultural heritage artefacts with CIDOC CRMdig | 1-gen-2020 | C.E. Catalano; V. Vassallo; S. Hermon; M. Spagnuolo | |
| Sea Monitoring Made Simple and Efficient | 1-gen-2020 | S. Berretta; D. Cabiddu; M. Mortara;M. Spagnuolo | |
| A pipeline for the preparation of artefacts that provides annotations persistence | 1-gen-2019 | Scalas, A; Mortara, M; Spagnuolo, M | |
| Context-adaptive navigation of 3D model collections | 1-gen-2019 | Biasotti, S; MOSCOSO THOMPSON, Elia; Spagnuolo, M | |
| Foreword to the special section on Eurographics workshop on 3D object retrieval 2017 | 1-gen-2018 | Lavoue, G; Pratikakis, I; Dupont, F; Ovsjanikov, M; Spagnuolo, M | |
| Supporting shared hypothesis testing in the biomedical domain. | 1-gen-2018 | A. Agibetov; E. JimenezRuiz; M. Ondresik; A. Solimando; I. Banerjee; G. Guerrini; C.E. Catalano; J.M. Oliveira; G. Patane; R.L Reis;M. Spagnuolo | |
| Topology-driven shape chartification | 1-gen-2018 | Tsorgente, ; Biasotti, S; Livesu, M; Spagnuolo, M | |
| Combination of visual and symbolic knowledge: A survey in anatomy | 1-gen-2017 | I. Banerjee; G. Patané;M. Spagnuolo | |
| Comparing methods for the approximation of rainfall fields in environmental applications | 1-gen-2017 | Patané, G; Cerri, A; Skytt, V; Pittaluga, S; Biasotti, S; Sobrero, D; Dokken, T; Spagnuolo, M | |
| Explicit cylindrical maps for general tubular shapes | 1-gen-2017 | Livesu, M; Attene, M; Patané, G; Spagnuolo, M | |
| 3D skeletons: a state-of-the-art report | 1-gen-2016 | Tagliasacchi, A; Delame, T; Spagnuolo, M; Amenta, N; Telea, A |