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X-WR-CALNAME:GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
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X-WR-CALDESC:évènements pour GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
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DTSTART:20250330T010000
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DTSTART;TZID=Europe/Paris:20250911T140000
DTEND;TZID=Europe/Paris:20250911T150000
DTSTAMP:20260419T024020
CREATED:20250902T083916Z
LAST-MODIFIED:20250908T083245Z
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SUMMARY:Séminaire Image : "Coreference Resolution in French Media"\, Kirill Milintsevich
DESCRIPTION:Nous aurons le plaisir d’écouter Kirill Milintsevich\, post-doctorant à l’Institut National de l’Audiovisuel (INA)\, Bry-sur-Marne.\nIl donnera un séminaire IMAGE le jeudi 11 septembre 2025 à 14h en salle de séminaire F-200. \nTitre : « Coreference Resolution in French Media » \nRésumé : \nThe Institut national de l’audiovisuel (INA) continuously records French TV and radio broadcasts\, creating a vast and invaluable archive for research in the humanities and social sciences. This dataset is particularly useful for studying real-world\, noisy conditions\, such as Automatic Speech Recognition (ASR) transcriptions.\nIn my postdoctoral project\, I evaluate both classic pretrained language models (PLMs) and large language models (LLMs) for automatic coreference resolution in ASR transcriptions of French broadcasts. Coreference resolution is a discourse processing task that identifies links between words in speech or text. For example\, in the phrase « John told Peter he was wrong\, » the pronoun « he » could refer to either « John » or « Peter\, » depending on the context. Automatic systems must resolve such ambiguities\, which is especially challenging in spoken language due to disfluencies and ASR errors.\nIn this talk\, I will provide an overview of automatic coreference resolution\, its unique challenges in French\, and the impact of ASR on performance. I will also present empirical results evaluating how well modern NLP models can address this task.
URL:https://www.greyc.fr/event/seminaire-image-coreference-resolution-in-french-media-kirill-milintsevich/
LOCATION:ENSICAEN – Batiment F – Salle F-200\, 6 Bd Maréchal Juin\, Caen\, 14050\, France
CATEGORIES:General,Image,News,Seminaire Image
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DTSTART;TZID=Europe/Paris:20250918T140000
DTEND;TZID=Europe/Paris:20250918T150000
DTSTAMP:20260419T024020
CREATED:20241201T161857Z
LAST-MODIFIED:20250610T093020Z
UID:11736-1758204000-1758207600@www.greyc.fr
SUMMARY:Séminaire Image : "Convergent Plug-and-Play methods to solve inverse problems"\, Nicolas Papadakis
DESCRIPTION:Nous aurons le plaisir d’écouter Nicolas Papadakis\, Institut de Mathématiques de Bordeaux.\nIl donnera un séminaire IMAGE le jeudi 18 septembre à 14h00 en salle de séminaire F-200. \nTitre : « Convergent Plug-and-Play methods to solve inverse problems » \nRésumé :\nIn image sciences\, Plug-and-Play methods constitute a class of iterative algorithms for solving inverse problems where regularization is performed by an off-the-shelf denoiser. Although Plug-and-Play methods can lead to tremendous visual performance for various image problems\, most existing convergence guarantees are based on unrealistic (or suboptimal) hypotheses on the denoiser\, or limited to strongly convex data terms. In this talk\, we discuss a type of Plug-and-Play method for which the denoiser is realized as a gradient descent step on a nonconvex functional parameterized by a deep neural network. Exploiting convergence results for proximal gradient descent algorithms in the non-convex setting\, we show that the proposed Plug-and-Play algorithm is a convergent iterative scheme that targets stationary points of an explicit global functional. Besides\, experiments show that it is possible to learn such a deep denoiser while not compromising the performance in comparison to other state-of-the-art deep denoisers used in Plug-and-Play schemes. The deep proximal gradient algorithms are applied to various ill-posed inverse problems\, e.g. deblurring\, super-resolution and inpainting. For all these applications\, numerical results empirically confirm the convergence results. Experiments also show that these algorithms reach state-of-the-art performance\, both quantitatively and qualitatively. \n 
URL:https://www.greyc.fr/event/seminaire-image-convergent-plug-and-play-methods-to-solve-inverse-problems-nicolas-papadakis/
LOCATION:ENSICAEN – Batiment F – Salle F-200\, 6 Bd Maréchal Juin\, Caen\, 14050\, France
CATEGORIES:General,Image,News,Seminaire Image
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