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Fraunhofer-Institut für Graphische Datenverarbeitung
For our Competence Center Smart Living and Biometric Technologies we’re looking for a

Master Thesis Proposal: Advancing metric-similarity learning

Kennziffer: IGD-2017-45
Biometrics is a rapidly growing technology that aims to identify or verify people identities based on their physical or behavioral properties. Machine learning approaches are the backbone of biometric recognition systems especially with approaches based on deep learning networks. This work aims at analyzing state of the art similarity learning approaches to propose a novel approach that addresses the disadvantages of previously proposed solutions.
Was Sie mitbringen
  • Interest in computer vision and machine learning
  • Programming skills
Study programs: Informatics, electrical engineering, mathematics, physics.
Was Sie erwarten können
This work will analyze existing similarity learning approaches in biometrics. A number of experiments (more than one biometric source) should be designed and implemented to evaluate the baseline state of the art similarity learning approaches. The achieved results should be analyzed and lead to new proposed similarity learning approach. Final evaluation and results should lead to in depth analyses and discussion on the topic.
Key literature:

[1] Karen Simonyan, Omkar M. Parkhi, Andrea Vedaldi, Andrew Zisserman: Fisher Vector Faces in the Wild. BMVC 2013.
[2] David Zhang, Yong Xu, Wangmeng Zuo: Metric Learning with Biometric Applications. Discriminative Learning in Biometrics pp 23-60.
[3] Dong Yi, Zhen Lei, Shengcai Liao, Stan Z. Li: Deep Metric Learning for Person Re-identification. ICPR 2014: 34-39

In case of identical qualifications, preference will be given to severely disabled candidates.
The Fraunhofer-Gesellschaft is committed to providing equal career opportunities for men and women.

Fraunhofer is Europe’s largest application-oriented research organization. Our research efforts are geared entirely to people’s needs: health, security, communication, energy and the environment. As a result, the work undertaken by our researchers and developers has a significant impact on people’s lives. We are creative. We shape technology. We design products. We improve methods and techniques. We open up new vistas.

Ansprechpartner: Naser Damer
Fraunhoferstr. 5
64283 Darmstadt
E-Mail: naser.damer@igd.fraunhofer.de
Fraunhofer-Institut für Graphische Datenverarbeitung


Erschienen auf academics.de am 31.08.2017
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