Archives: Thesis

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27MAR 2020
News
Pattern Recognition Lab embraces Online Teaching
Over the years, we have collected a rather large collection of online teaching material that we now also highlight on our Teaching Section. One feature is the Deep Learning Material with video lectures and online experimentation environments on various topics. Another gem is the new version of the LME Video Section which now features Tutorials, […]
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26MAR 2020
News
Two Projects submitted to EU Call DT-TRANSFORMATIONS-12
On Thursday, the 19th of March 2020, we submitted two 3 Million EUR grants to the European Commission. One project aims at building a European Network to establish Book CT as a method to access cultural information in historical books non-invasively from Scanning over Handwritten-Text-Recognition and Writer Identification to Knowledge Modelling. The other project, Odeuropa, […]
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25MAR 2020
News
MICCAI 2020 Deadline Passed – 17 Full Submissions
It is a pleasure to announce that the Pattern Recognition Lab managed to complete an astounding 17 full submissions for MICCAI 2020 in Lima, Peru! This is a great success given the adversarial conditions during the current time of corona crisis. Now the review phase of the 1816 submitted papers begins. More than 1400 experts from […]
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25MAR 2020
News
Pattern Recognition Lab – COVID-19 Measures
The Pattern Recognition Lab is engaged to combat the global COVID-19 pandemic. In order to limit the spread, we engaged in the following measures: Exams postponed: All written, oral and PhD exams are postponed until further notice. This measure is extreme. Therefore, we will be flexible in taking exams as soon as they are possible […]
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15FEB 2020
Datasets
Large-scale pathology dataset for mitotic figure detection
We released a large-scale data set for mitotic figure detection as open data. Unlike previous data sets, it is the only data set that provides a complete annotation map for the histology whole slide image. It includes 44880 mitotic figures, verified in blind review by two expert pathologists. We were able to show that the […]
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06FEB 2020
News
BMBF to fund joint project on MR Imaging and Deep Learning in Cooperation with University of Würzburg
We are proud to announce the funding of “Intelligent MR Diagnosis of the Liver by Linking Model and Data-driven Processes (iDELIVER)“ by BMBF. The project examines the use and further development of machine learning methods for MR image reconstruction and for the classification of liver lesions. Based on a comparison model and data-driven image reconstruction […]
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