480 search results for “boer image” in the Public website
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Veerle BoerFaculty of Social and Behavioural Sciences
v.j.boer@fsw.leidenuniv.nl |
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Gabe BoerASSC
g.j.g.m.boer@assc.leidenuniv.nl | 071 5272727
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Renske de BoerFaculteit der Rechtsgeleerdheid
r.de.boer.12@law.leidenuniv.nl |
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Koos BoerFaculteit der Rechtsgeleerdheid
j.p.boer@law.leidenuniv.nl | 071 5278875
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Jelle de BoerStudent and Educational Support
j.j.de.boer@sea.leidenuniv.nl |
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Roan de BoerISSC
r.j.de.boer@issc.leidenuniv.nl |
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Steinn de BoerFaculteit der Rechtsgeleerdheid
s.w.de.boer@law.leidenuniv.nl | 071 5272727
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Jacqueline de BoerFaculty of Science
deboer@lorentzcenter.nl | 071 5275585
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Fianne de BoerStudent and Educational Support
f.e.de.boer@sea.leidenuniv.nl |
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Joris de BoerFaculty of Social and Behavioural Sciences
j.de.boer@fsw.leidenuniv.nl | 071 5272727
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Mara BoersFaculty of Science
m.w.e.j.boers.2@umail.leidenuniv.nl |
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Marlies de BoerAdministration and Central Services
mac.deboer@bb.leidenuniv.nl | 071 5273307
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Edith den BoerASSC
e.l.den.boer@assc.leidenuniv.nl | 071 5275555
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Frank de BoerFaculty of Science
f.s.de.boer@liacs.leidenuniv.nl | 071 5272727
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Hannah de BoerFaculty of Social and Behavioural Sciences
h.c.de.boer@fsw.leidenuniv.nl | 071 5272727
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Elizabeth den BoerFaculty of Humanities
e.p.den.boer@hum.leidenuniv.nl | 070 8009500
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Maria de Boer -
Monica den BoerFaculty of Governance and Global Affairs
m.g.w.den.boer@fgga.leidenuniv.nl | 070 8009500
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Meike de BoerFaculty of Humanities
m.m.de.boer@hum.leidenuniv.nl | 071 5272727
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Hester de BoerFaculteit der Rechtsgeleerdheid
h.de.boer@law.leidenuniv.nl | 071 5272727
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Mark de BoerFaculty of Medicine
m.g.j.de_boer@lumc.nl | 071 5262613
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Elpine de BoerFaculty of Humanities
e.de.boer@hum.leidenuniv.nl | 071 5272562
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Thijs de Boer -
Eveline de BoerICLON
e.de.boer@iclon.leidenuniv.nl | 071 5271748
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Jill den BoerFaculty of Science
m.j.den.boer@cml.leidenuniv.nl | 071 5272727
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Bertram de Boer -
Connie de Boer-LindemanFaculty of Science
c.m.t.de.boer@umail.leidenuniv.nl | 071 5275144
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Eveline de Boer-MeuldijkFaculty of Humanities
e.de.boer.4@hum.leidenuniv.nl | 071 5273294
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Imaging
The imaging group focuses on bio-imaging, image analysis and visualization.
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Image-based Computational Biology
In this research group, led by Dr. Joost Beltman, the aim is to employ mathematical and computational dynamical modelling approaches in order to quantitatively and mechanistically understand the dynamical behaviour and regulation of intracellular networks of genes, proteins and metabolites as well as…
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Biomedical Imaging
The rapid advances in imaging technology enable to see inside the body with ever increasing detail.
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Deep imaging
A computer can look at, and learn from, many more images than a human specialist. AI systems are rapidly becoming indispensable for medical and biological applications. But they still have to learn how to explain their decisions.
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High-Contrast Imaging of Protoplanetary Disks
To study how planetary systems come into existence we study much younger systems still in formation.
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Imaging & Intervention (MSc)
This specialisation focuses on two important trends in health care: early diagnosis and developing the most targeted patient-specific treatment possible with the shortest possible recovery time and minimal side effects.
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Vision and Imaging
On the basis of the characteristic aspects of a picture, certain computers can tell us what the picture is showing. They can learn this in the same way that young children are able to learn to recognize images. Further improving these techniques opens the way to a whole range of new applications. Biology…
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Imaging and Bioinformatics
On the basis of the characteristic aspects of a picture, certain computers can tell us what the picture is showing. They can learn this in the same way that young children are able to learn to recognize images. Further improving these techniques opens the way to a whole range of new applications. Biology…
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Images of Galois representations
Promotores: S.J. Edixhoven, P.Parent
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Gold nanorod photoluminescence: applications to imaging and temperature sensing
Promotor: M.A.G.J. Orrit
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Deep Learning Solutions for Domain-Specific Image Segmentation
Image segmentation is a fundamental task in computer vision, with applications ranging from medical diagnostics to archaeological research.
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Detection of Archaeological Sites in High Resolution Satellite Images
In this project we develop algorithms to automatically detect a particular type of archaeological sites in satellite images of the Alps.
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Computational optimisation of optical projection tomography for 3D image analysis
Optical projection tomography (OPT) is a tomographic 3D imaging technique used for specimens in the millimetre scale.
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On the optimization of imaging pipelines
In this thesis, topics relating to the optimization of high-throughput pipelines used for imaging are discussed. In particular, different levels of implementation, i.e., conceptual, software, and hardware, are discussed and the thesis outlines how advances on each level need to be made to make gains…
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Image and Identity in Chinese Historic Houses
How and to what extent the historic house (re-)constructs identity through image-making in China.
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Exploring Deep Learning for Intelligent Image Retrieval
This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.
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Time Domain Imaging of Transient and Variable Radio Sources
This thesis focuses on the study of transient and variable radio sources in the universe.
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Uulke van der HeideFaculty of Medicine
u.a.van_der_heide@lumc.nl | 071 5269111
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Imaging complex model catalysts in action
From surface science towards industrial practice using high-pressure scanning tunneling microscopy.
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Culture: text and images in Japan
One of the ways of understanding another culture better is to examine what people experience when they read a text, or look at an image. Leiden experts have a lot of knowledge in this field, for example on culture in ancient Japan.
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Painting with starlight : optical techniques for the high-contrast imaging of exoplanets
This thesis describes the development and validation of new high-contrast imaging techniques, with the ultimate goal of enabling the next generation of instruments for ELT-class telescopes to directly image Earth-like extra-solar planets orbiting around nearby stars.
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Suppressing a Sea of Starlight: Enabling technology for the direct imaging of exoplanets
Promotor: Christoph U. Keller, Co-promotores: Matthew A. Kenworthy, Frans Snik