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Tailorable Sampling for Progressive Visual Analytics

Autor: Marius Hogräfer, Hans-Jörg Schulz

Publikováno v: Hogräfer, M & Schulz, H-J 2023, ' Tailorable Sampling for Progressive Visual Analytics ', IEEE Transactions on Visualization and Computer Graphics, vol. PP, pp. 1-13 . https://doi.org/10.1109/TVCG.2023.3278084

Progressive visual analytics (PVA) allows analysts to maintain their flow during otherwise long-running computations by producing early, incomplete results that refine over time, for example, by running the computation over smaller partitions of the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2b341f912936e25e225875ddc9d3cf6
https://pure.au.dk/portal/da/publications/tailorable-sampling-for-progressive-visual-analytics(c991982c-7c6a-43bf-8684-7e6f1d790b01).html

Towards an Uncertainty-Aware Visualization in the Digital Humanities

Autor: Roberto Therón Sánchez, Alejandro Benito Santos, Rodrigo Santamaría Vicente, Antonio Losada Gómez

Publikováno v: Informatics, Vol 6, Iss 3, p 31 (2019)

As visualization becomes widespread in a broad range of cross-disciplinary academic domains, such as the digital humanities (DH), critical voices have been raised on the perils of neglecting the uncertain character of data in the visualization design

Externí odkaz: https://doaj.org/article/4cb1ece180624dffa261ae3b37871956

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A Neural Signal Processor for Low-Latency Spike Inference

Autor: Lai, Chongxi

This thesis describes the development of a system that can assign identities to a population of single-units, in multi-electrode recordings, at single-spike resolution with low-latency. The system has two parts. The first is a Field-Programmable Gate

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ef5ddae1aeacfeb2d84836cfcec0dc3c