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dc.contributor.author | Capozzi, Luigi | es_ES |
dc.contributor.author | Arsiccio, Andrea | es_ES |
dc.contributor.author | Sparavigna, Amelia | es_ES |
dc.contributor.author | Pisano, Roberto | es_ES |
dc.contributor.author | Barresi, Antonello | es_ES |
dc.date.accessioned | 2019-03-05T07:22:21Z | |
dc.date.available | 2019-03-05T07:22:21Z | |
dc.date.issued | 2018-09-07 | |
dc.identifier.isbn | 9788490486887 | |
dc.identifier.uri | http://hdl.handle.net/10251/117655 | |
dc.description.abstract | [EN] In a freeze drying process, the freezing step determines the pore size distribution within the product, which, in turn, affects the sublimation rate. Traditionally, pore analysis is carried out on SEM images by means of a manual, time-consuming approach. Here, an image segmentation technique was used to automatize this process and improve its reliability. A 3D structure of the cake was then reconstructed from the distribution of the super-pixels. We show that the approach herein proposed can remarkably improve prediction of the sublimation rate with respect to traditional methods. | es_ES |
dc.description.sponsorship | Computational resources were provided by ISCRA-Cineca HPC CLASS-C Grant to L.C.C. (ParticLy - HP10CQRVJV) | es_ES |
dc.format.extent | 8 | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Editorial Universitat Politècnica de València | es_ES |
dc.relation.ispartof | IDS 2018. 21st International Drying Symposium Proceedings | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | Drying | es_ES |
dc.subject | Dehydration | es_ES |
dc.subject | Dewatering | es_ES |
dc.subject | Emerging technologies | es_ES |
dc.subject | Products quality | es_ES |
dc.subject | Process control | es_ES |
dc.subject | Environmental | es_ES |
dc.subject | Evaporation | es_ES |
dc.subject | Sublimation | es_ES |
dc.subject | Diffusion | es_ES |
dc.subject | Energy | es_ES |
dc.subject | Intensification | es_ES |
dc.subject | Freezing | es_ES |
dc.subject | Freeze-drying | es_ES |
dc.subject | Image segmentation | es_ES |
dc.subject | 3D reconstruction | es_ES |
dc.title | Image Segmentation and 3D reconstruction for improved prediction of the sublimation rate during freeze drying | es_ES |
dc.type | Capítulo de libro | es_ES |
dc.type | Comunicación en congreso | es_ES |
dc.identifier.doi | 10.4995/IDS2018.2018.7646 | |
dc.relation.projectID | info:eu-repo/grantAgreement/ISCRA//HP10CQRVJV/ | |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Capozzi, L.; Arsiccio, A.; Sparavigna, A.; Pisano, R.; Barresi, A. (2018). Image Segmentation and 3D reconstruction for improved prediction of the sublimation rate during freeze drying. En IDS 2018. 21st International Drying Symposium Proceedings. Editorial Universitat Politècnica de València. 411-418. https://doi.org/10.4995/IDS2018.2018.7646 | es_ES |
dc.description.accrualMethod | OCS | es_ES |
dc.relation.conferencename | 21st International Drying Symposium | es_ES |
dc.relation.conferencedate | Septiembre 11-14, 2018 | es_ES |
dc.relation.conferenceplace | Valencia, Spain | es_ES |
dc.relation.publisherversion | http://ocs.editorial.upv.es/index.php/IDS/ids2018/paper/view/7646 | es_ES |
dc.description.upvformatpinicio | 411 | es_ES |
dc.description.upvformatpfin | 418 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.relation.pasarela | OCS\7646 | es_ES |
dc.contributor.funder | Italian SuperComputing Resource Allocation |