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X-WR-CALNAME:GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
X-ORIGINAL-URL:https://www.greyc.fr
X-WR-CALDESC:évènements pour GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
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TZID:Europe/Paris
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DTSTART:20230326T010000
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DTSTART:20231029T010000
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20230912T100000
DTEND;TZID=Europe/Paris:20230912T110000
DTSTAMP:20260629T005242
CREATED:20230911T082936Z
LAST-MODIFIED:20230911T082936Z
UID:11241-1694512800-1694516400@www.greyc.fr
SUMMARY:Séminaire Algorithmique : Ana Maria Costache (NTNU\, Trondheim\, Norvège) « FHE Circuit Privacy for Free »
DESCRIPTION:Circuit privacy is an important notion in Fully Homomorphic Encryption (FHE)\, well-illustrated by the Machine Learning-as-a-Service scenario. A scheme is circuit private if an adversary cannot learn the circuit evaluated on a ciphertext from the computation result. In this talk\, we show that the FHE scheme BGV is computationally circuit private in a semi-honest context. \nIn more detail\, we first introduce the notions of FHE and the BGV scheme. Then\, we define computational circuit privacy and argue why this definition is strong enough for our purpose. We then show that BGV naturally fulfills this definition and\, furthermore\, that if the adversary is assumed to have the secret key\, it may learn information about the circuit even if the scheme is proven to be circuit private. We therefore\, propose a new definition of computational circuit privacy to capture this as well. We prove that through modulus switching ciphertexts in strategic places\, we can achieve this new definition without the need for any additional expensive machinery. \nJoint work with Lea Nürnberger and Tjerand Silde.
URL:https://www.greyc.fr/event/seminaire-algorithmique-ana-maria-costache-ntnu-trondheim-norvege-fhe-circuit-privacy-for-free/
LOCATION:Sciences 3- S3 351
CATEGORIES:General,News,Séminaire Algo
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20230914T140000
DTEND;TZID=Europe/Paris:20230914T140000
DTSTAMP:20260629T005242
CREATED:20230908T093039Z
LAST-MODIFIED:20230910T152554Z
UID:11236-1694700000-1694700000@www.greyc.fr
SUMMARY:Séminaire IMAGE : « Digital topology constraints in computational anatomy models of embryonic human brains » (Akinobu Shimizu\, Tokyo University of Agriculture and Technology)\, et « On the distribution of texture in the nuclei of follicular cells in malignant lymphoma » (Hidekata Hontani\, Nogoya Institute of Technology)
DESCRIPTION:Nous aurons le plaisir d’écouter Akinobu Shimizu (Tokyo University of Agriculture and Technology) et Hidekata Hontani (Nogoya Institute of Technology)\, qui donneront un séminaire IMAGE\, le jeudi 14 septembre 2023\, à 14h00\, en salle de séminaire F-200.\n\nIl s’agira de deux séminaires qui se suivent\, d’une demi-heure chacun\, dont les sujets sont :\n\n\n1 ) Digital topology constraints in computational anatomy models of embryonic human brains\nAkinobu Shimizu (Tokyo University of Agriculture and Technology) \nThe human body exhibits nested structures\, including ventricles that envelop chorioid plexuses. Employing topological constraints proves valuable in building a computational anatomy model that captures statistical variations within these nested constraints. Diffeomorphism represents a common method for managing such constraints\, but it falls short when it comes to depicting the appearance and vanishing of anatomical structures in embryonic human brains\, like chorioid plexuses\, which emerge post-Carnegie stage 19. \nThis presentation introduces an approach for depicting the statistical variations in anatomical structures while considering both nested and neighboring constraints. The utilization of a signed distance-based approach enables us to describing the appearance and disappearance of anatomical structures within these constraints. We apply this proposed method to construct a spatio-temporal statistical model encompassing the surfaces of the brain\, ventricles\, and chorioid plexuses in human embryos. \n  \n2) Dynamic PET Image Reconstruction Using Nonnegative Matrix Factorization Incorporated with Deep Image Prior\nHidekata Hontani (Nogoya Institute of Technology) \nWe propose a method that reconstructs dynamic positron emission tomography (PET) images from given sinograms by using non-negative matrix factorization incorporated with a deep image prior for appropriately constraining the spatial patterns of resultant images. The proposed method can reconstruct dynamic PET images with higher signal- to-noise ratio and blindly decompose an image matrix into pairs of spatial and temporal factors. The former represents homogeneous tissues with different kinetic parameters and the latter represent the time activity curves that are observed in the corresponding homogeneous tissues. We employ U-Nets combined in parallel for deep image prior and each of the U-Nets is used to extract each spatial factor decomposed from the data matrix. Experimental results show that the proposed method outperforms conventional methods and can extract spatial factors that represent the homogeneous tissues. \n\n\nOn vous attend nombreux!
URL:https://www.greyc.fr/event/seminaire-image-digital-topology-constraints-in-computational-anatomy-models-of-embryonic-human-brains-akinobu-shimizu-tokyo-university-of-agriculture-and-technology-et/
LOCATION:ENSICAEN – Batiment F – Salle F-200\, 6 Bd Maréchal Juin\, Caen\, 14050\, France
CATEGORIES:Image,Seminaire Image
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20230926T100000
DTEND;TZID=Europe/Paris:20230926T110000
DTSTAMP:20260629T005242
CREATED:20230911T083129Z
LAST-MODIFIED:20230922T072033Z
UID:11244-1695722400-1695726000@www.greyc.fr
SUMMARY:Séminaire Algorithmique : « Ten asymptotic expansions for the Stirling numbers of the second kind » Hsien-Kuei Hwang (Academia Sinica\, Taipei\, Taiwan)
DESCRIPTION:In this talk\, I will first review existing asymptotic approximations in the literature for the Stirling partition numbers (or Stirling numbers of the second kind)\, the list of references being by far the most complete one. Then I will present a general\, systematic\, elementary approach to generate ten different asymptotic expansions whose uniformity covers particularly the central range (with most mass of the distribution lies). These expansions represent the first such ones in the literature that are rigorously justified. \nThis talk is based on joint work with Chong-Yi Li and Vytas Zacharovas.
URL:https://www.greyc.fr/event/seminaire-algorithmique-hsien-kuei-hwang-academica-sinica-taipei-taiwan/
LOCATION:Sciences 3- S3 351
CATEGORIES:General,News,Séminaire Algo
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