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Institution

Brno University of Technology

EducationBrno, Czechia
About: Brno University of Technology is a education organization based out in Brno, Czechia. It is known for research contribution in the topics: Fracture mechanics & Filter (video). The organization has 6339 authors who have published 15226 publications receiving 194088 citations. The organization is also known as: Vysoké učení technické v Brně & BUT.


Papers
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Journal ArticleDOI
TL;DR: A general framework for incremental maximum likelihood estimation called SLAM++ is introduced, which fully benefits from the incremental nature of the online applications, and provides efficient estimation of both the mean and the covariance of the estimate.
Abstract: The most common way to deal with the uncertainty present in noisy sensorial perception and action is to model the problem with a probabilistic framework. Maximum likelihood estimation is a well-kno...

77 citations

Journal ArticleDOI
TL;DR: This work designs optimized protein sequences that maximize stability, solubility, and activity over a wide range of temperatures and pH values in buffers of different composition and in the presence of organic cosolvents.
Abstract: Natural enzymes are delicate biomolecules possessing only marginal thermodynamic stability. Poorly stable, misfolded, and aggregated proteins lead to huge economic losses in the biotechnology and b...

77 citations

Journal ArticleDOI
TL;DR: In this paper, the impact of waste to energy (WTE) regarding the environmental issue is quantified in terms of primary energy savings and an assessment of the emission rate is made and results discussed.

77 citations

Proceedings ArticleDOI
15 Sep 2019
TL;DR: This paper presents a simplified version of the previously proposed diarization algorithm based on Bayesian Hidden Markov Models, which uses Variational Bayesian inference for very fast and robust clustering of x-vector (neural network based speaker embeddings).
Abstract: This paper presents a simplified version of the previously proposed diarization algorithm based on Bayesian Hidden Markov Models, which uses Variational Bayesian inference for very fast and robust clustering of x-vector (neural network based speaker embeddings). The presented results show that this clustering algorithm provides significant improvements in diarization performance as compared to the previously used Agglomerative Hierarchical Clustering. The output of this system can be further employed as an initialization for a second stage VB diarization system, using frame-wise MFCC features as input, to obtain optimal results.

77 citations

Journal ArticleDOI
TL;DR: Transmitted-light coherence-controlled holographic microscope based on an off-axis achromatic interferometer provides high quality (speckle-free) imaging, improved lateral resolution and optical sectioning by coherence gating and their limits for a technical realization are derived and described in detail.
Abstract: Transmitted-light coherence-controlled holographic microscope (CCHM) based on an off-axis achromatic interferometer allows us to use light sources of arbitrary degree of temporal and spatial coherence. Besides the conventional DHM modes such as quantitative phase contrast imaging and numerical 3D holographic reconstruction it provides high quality (speckle-free) imaging, improved lateral resolution and optical sectioning by coherence gating. Optical setup parameters and their limits for a technical realization are derived and described in detail. To demonstrate the optical sectioning property of the microscope a model sample uncovered and then covered with a diffuser was observed using a low-coherence light source.

77 citations


Authors

Showing all 6383 results

NameH-indexPapersCitations
Georg Kresse111430244729
Patrik Schmuki10976352669
Michael Schmid8871530874
Robert M. Malina8869138277
Jiří Jaromír Klemeš6456514892
Alessandro Piccolo6228414332
René Kizek6167216554
George Danezis5920911516
Stevo Stević583749832
Edvin Lundgren5728610158
Franz Halberg5575015400
Vojtech Adam5561114442
Lukas Burget5325221375
Jan Cermak532389563
Hynek Hermansky5131714372
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202328
2022106
20211,053
20201,010
20191,214
20181,131