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Reference : UMR5672-NELPUS-001
Workplace : LYON 07
Date of publication : Thursday, January 09, 2020
Scientific Responsible name : Nelly Pustelnik
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 September 2020
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly
Description of the thesis topic
Interface detection is a challenging question in image processing, and more generally in graph processing, leading to a large panel of applications going from geophysics research to societal studies. The common point to these applications is the willingness to have an interface detection at a fine scale, possibly with subpixel accuracy, in order to extract interpretable parameters (e.g. physical or societal), from high resolution data.
This PhD is devoted to the development of innovative image/graph processing tools relying both on optimization and multiresolution analysis in order to provide a new paradigm for the interface detection on large scale data. This project essentially relies on:
* a deep theoretical study of the discrete Mumford-Shah (MS) model to perform accurate interface detection, and thus measure precise interface length;
* the design of multiscale proximal algorithms to make possible the implementation of the discrete Mumford-Shah model on large scale data;
* the study of alternative solutions relying on deep learning strategies.
The PhD will take place at Laboratoire de Physique, ENS de Lyon (France) and UCLouvain, both very attractive and dynamic research environments.
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