Philipp Harzig
Research Assistant & PhD Student
Chair for Multimedia Computing and Computer Vision Lab
| Phone: | +49 (821) 598 4334 |
| Email: | philipp.harzig@informatik.uni-augsburg.de |
| Room: | 1024 (N) |
| Visiting hours: | By appointment |
| Address: | Universitätsstraße 6a, 86159 Augsburg |
Research Interests
- Computer Vision
- Machine Learning
- Visual Question Answering
- Image Captioning
- Deep Convolutional Neural Networks
- Recurrent Neural Networks
- Machine Learning Optimization
Projects
- Automatic Image Captioning of Scenes Depicting Branded Products
- Company Logo Detection
Publications
- Philipp Harzig, Moritz Einfalt, Rainer Lienhart.
BioMedia Grand Challenge: Automatic Disease Detection and Report Generation for Gastrointestinal Tract Examinations.
ACM Multimedia (ACMMM) 2019. Nice, France, October 2019, to appear - Philipp Harzig, Yan-Ying Chen, Francine Chen, Rainer Lienhart.
Addressing Data Bias Problems for Chest X-ray Image Report Generation.
British Machine Vision Conference (BMVC) 2019. Cardiff, UK, September 2019, [arXiv] - Philipp Harzig, Dan Zecha, Rainer Lienhart, Carolin Kaiser, René Schallner.
Image Captioning with Clause-Focused Metrics in a Multi-Modal Setting for Marketing.
IEEE MIPR 2019 San José, CA, USA, March 2019 [ PDF] - Philipp Harzig, Christian Eggert, Rainer Lienhart.
Visual Question Answering With a Hybrid Convolution Recurrent Model.
ACM International Conference on Multimedia Retrieval 2018 (ACM ICMR 2018) Yokohama, June 2018 [ PDF] - Philipp Harzig, Stephan Brehm, Rainer Lienhart, Carolin Kaiser, René Schallner.
Multimodal Image Captioning for Marketing Analysis.
IEEE MIPR 2018 Miami, FL, USA, April 2018 [ PDF]
Master Thesis
Philipp Harzig.
Implementation of Frequency Domain Convolution for the Caffe-Framework.
Master Thesis, February 2016.
Teaching
- WS 2019/2020: Advanced Deep Learning [ Digicampus]
- WS 2019/2020: Grundlagen der Signalverarbeitung und des Maschinellen Lernens (Multimedia Grundlagen I) [ Digicampus]
- WS 2019/2020: Grundlagen der Signalverarbeitung und des Maschinellen Lernens für Medizininformatiker [ Digicampus]
- SS 2019: Advanced Deep Learning [ Digicampus]
- WS 2018/2019: Advanced Deep Learning [ Digicampus]
- SS 2018: Praktikum über Autonomes Fahren [ Digicampus]
- SS 2018: Multimedia II: Machine Learning & Computer Vision
- WS 2017/2018: Multimedia Grundlagen I
- SS 2017: Praktikum über Autonomes Fahren [ Digicampus]
- SS 2017: Multimedia II: Machine Learning & Computer Vision
- WS 2016/2017: Multimedia Grundlagen I
- SS 2016: Multimedia II: Machine Learning & Computer Vision