microscopy – PhD Seminars

Étiquette : microscopy

Café ADSTIC: Seeing inside a living cell: digital glasses to the aid of the microscope

Café ADSTIC: Seeing inside a living cell: digital glasses to the aid of the microscope

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2:00 pm: PhD Seminars VII

2:00 pm: PhD Seminars VIII

Sujets d’intérêt

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Calendar

2:00 pm: PhD Seminars VII

2:00 pm: PhD Seminars VIII

Talk 1

Talk 2

Talk 1

Talk 1

Talk 2

Talk 1

Nathalie GAYRAUD Tue 09 May 2017 Tue 09 May 2017Annonces

Hello everyone, Following the success of the previous C@fés ADSTIC, we invite you to come to the next one! We will be pleased to welcome Laure Blanc-Féraud who will talk about: « Seeing inside a living cell: digital glasses to the aid of the microscope ». Laure Blanc-Féraud is a CNRS…

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Sujets d’intérêt
applied mathematics asteroid exploration biological systems brain combinatorial optimization communication conductivity estimation dynamic dynamics EEG fixed point loops fluid dynamics functional emmbeddings fusion plasmas Galerkin time domain methods git health-biology infection spread invariant manifolds mapping marketing mesh modeling nanophotonics networks networks-systems-distributed-computing neuronal cells numerical simulations optimal transport optimisation optimization pattern recognition PDE protein function radar applications regularization retina routing applications scientific dissemination sed shape matching source localization stochastic gradient algorithm variability workshop
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12 2:00 pm: PhD Seminars VIII avril 12, 2021 2:00 – 4:00 Talk 1 Speaker Maroua Tikat (WIMMICS) Title Interactive multimedia visualization for exploring and fixing a multi-dimensional metadata base of popular music Abstract This PHD thesis is concerned by the use of information visualization techniques as a mean to allow the exploration of a large dataset of music metadata. In this paper we review some of the major music datasets available, the data they contain, and how information visualization techniques have been used to explore such data. As we shall see, music is a complex entity that can be described as a multitude of multimedia attributes (ex. lyrics, chords, audio, graphics describing sound analysis, etc.). Thus, music datasets are often created by collecting data from specialized datasets. The integration of data from diverse sources might create problems of data quality (ex. ambiguities, imprecision, incomplete sources, conflicts, etc.). Traditionally, information visualization techniques are used to understand the corpus of data and identify causal relationships, trends, patterns of data concentrations. Nonetheless, we suggest that information visualization techniques be used to inspect the data quality of multivariate data sets and highlight the parts of the data sets that need to be fixed/improved. Moreover, using interactive techniques, we suggest that information visualization techniques could be used as entry point for repairing the data set. In the context of this PhD thesis, the research questions are: how to communicate problems related to data quality to the users, and how to visually represent the outcomes of methods used for data completion and correction (such as crowdsourcing, matrix vectorization, graph reasoning, among other). More