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ORCIDChristopher Pramerdorfer
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2020 – today
- 2020
[c10]Christopher Pramerdorfer, Rainer Planinc, Martin Kampel
:
Effective Deep-Learning-Based Depth Data Analysis on Low-Power Hardware for Supporting Elderly Care. CVPR Workshops 2020: 1584-1590- [c9]Christopher Pramerdorfer, Julian Strohmayer, Martin Kampel:
Sdt: A Synthetic Multi-Modal Dataset For Person Detection And Pose Classification. ICIP 2020: 1611-1615 - [c8]Christopher Pramerdorfer, Martin Kampel:
Deep Body-pose Estimation via Synthetic Depth Data: A Case Study. VISIGRAPP (5: VISAPP) 2020: 318-325
2010 – 2019
- 2019
- [c7]Christopher Pramerdorfer, Martin Kampel, Reinhard Kreissl:
Behavior detection as a privacy-enhancing security technology in prison cells. ICDP 2019: 1-6 - 2018
- [c6]Christopher Pramerdorfer, Martin Kampel, Mark Van Loock:
Multi-View Classification and 3D Bounding Box Regression Networks. ICPR 2018: 734-739 - 2017
- [c5]Christopher Pramerdorfer, Martin Kampel:
Deep Objective Image Quality Assessment. CAIP (2) 2017: 127-138 - 2016
- [c4]Christopher Pramerdorfer, Rainer Planinc, Mark Van Loock, David Fankhauser, Martin Kampel, Michael Brandstötter:
Fall Detection Based on Depth-Data in Practice. ECCV Workshops (2) 2016: 195-208 - [c3]Paolo Rota, Enver Sangineto, Valentina Conotter, Christopher Pramerdorfer:
Bad teacher or unruly student: Can deep learning say something in Image Forensics analysis? ICPR 2016: 2503-2508 - [i1]Christopher Pramerdorfer, Martin Kampel:
Facial Expression Recognition using Convolutional Neural Networks: State of the Art. CoRR abs/1612.02903 (2016) - 2015
- [c2]Christopher Pramerdorfer, Martin Kampel:
A dataset for computer-vision-based PCB analysis. MVA 2015: 378-381 - [c1]Christopher Pramerdorfer, Martin Kampel:
PCB Recognition using Local Features for Recycling Purposes. VISAPP (3) 2015: 71-78
Coauthor Index
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