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Michael Opitz

Dipl.-Ing., BSc

20162019
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Fingerprint Dive into the research topics where Michael Opitz is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 21 Similar Profiles
Data storage equipment Engineering & Materials Science
Computer vision Engineering & Materials Science
Cameras Engineering & Materials Science
Neural networks Engineering & Materials Science

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Research Output 2016 2019

  • 10 Conference contribution
  • 3 Article

HiBsteR: Hierarchical Boosted Deep Metric Learning for Image Retrieval

Waltner, G., Opitz, M., Possegger, H. & Bischof, H., 8 Jan 2019, (Submitted) 2019 IEEE Winter Conference on Applications of Computer Vision (WACV) .

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Semi-supervised Detector Training with Prototypes for Vehicle Detection

Waltner, G., Opitz, M., Krispel, G., Possegger, H. & Bischof, H., Jun 2019, (Accepted/In press) 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019. Institute of Electrical and Electronics Engineers, 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

An Intent-Based Automated Traffic Light for Pedestrians

Ertler, C., Possegger, H., Opitz, M. & Bischof, H., 2018, (Accepted/In press) IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Deep 2.5D Vehicle Classification with Sparse SfM Depth Prior for Automated Toll Systems

Waltner, G., Maurer, M., Holzmann, T., Ruprecht, P., Opitz, M., Possegger, H., Fraundorfer, F. & Bischof, H., 7 Dec 2018, 2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018. Institute of Electrical and Electronics Engineers, Vol. 2018-November. p. 3212-3217 6 p. 8569670

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Computer vision
Cameras
Neural networks
Data storage equipment

Deep 2.5 D Vehicle Classification with Sparse SfM Depth Prior for Automated Toll Systems

Waltner, G., Maurer, M., Holzmann, T., Ruprecht, P., Opitz, M., Possegger, H., Fraundorfer, F. & Bischof, H., 2018, In : arXiv.org e-Print archive. 6 p.

Research output: Contribution to journalArticleResearchpeer-review