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Patterns in One Health – Oct 24/25, 2023, Meduni Vienna
The Austrian Association for Pattern Recognition (OAGM) invites authors and guests to participate in its 46th annual workshop, held on October 24 and 25, 2023 at Meduni Vienna in the beautiful Van Swieten Saal.
The workshop will bring together the interdisciplinary scientific community in the areas of machine learning, artificial intelligence, computer vision, and biomedicine in Austria and nearby countries to present and discuss recent research and the most important directions in this rapidly evolving field, with impact across many disciplines. This year, we have defined an interdisciplinary impulse theme of one health to engage and build a bridge to the fields of pattern recognition and machine learning.
Registration: please register via an email to workshop@aapr.at giving your Name and Institution. The registration fee is €250, and will be invoiced individually.
Invited speakers and Panelists:
- Christoph Bock: Programmed Cells? Machine learning for molecular precision medicine
CeMM & Medical University of Vienna - Gerhard Ecker: In silico Prediction of Toxicity – from QSAR models to biological Fingerprinting
University of Vienna - Joel Podgorski: Estimating geogenic groundwater quality hazard and health risk using spatial prediction modeling
EAWAG Aquatic Resaerch - Enrique Estrada Lobato
IAEA, UNO - Chris Russ
AWS
Preliminary programme:
Venue: Van Swieten Saal der Medizinischen Universität Wien, Van-Swieten-Gasse 1a, 1090 Wien
How to get there: link
AAPR’23 Patterns in One Health is sponsored by
Important Dates:
- Paper submission deadline: September 12, 2023 (firm)
- Notification of acceptance: October 9, 2023
- Final papers due: October 17, 2023 (firm)
- Workshop: October 24/25, 2023
Contact:
Conference Chairs:
- Georg Langs (Computational Imaging Research Lab, Meduni Vienna)
- Peter M. Roth (Institute of Computational Medicine, VetMedUni Vienna)
- Roxane Licandro (Computational Imaging Research Lab, Meduni Vienna)
Organizing Committee
- Florian Kleber (Computer Vision Lab, TU Vienna)
- Ezo Stefanovic (Computational Imaging Research Lab, MedUni Vienna)
Location:
The workshop will be held in the Van Swieten Saal at the Medical University of Vienna
Publication:
Accepted papers and spotlight abstracts will be published online with Verlag der TU Graz in a fully open-access electronic volume (with ISBN, and DOIs for individual papers and abstracts).
Download a copy of this call for papers: CfP
Submission platform: submission is closed. Notifications will go out shortly
https://cmt3.research.microsoft.com/OAGM2023
following the format given in the official template (LaTex and Word). For camera-ready submission, please also upload the official Publishing Agreement form.
Submission formats:
To encourage the linking across communities active in the subject areas, we solicit (1) Full papers (max. 6 pages): novel, original, unpublished work. (2 ) Spotlight abstracts (max. 2 pages including one figure): exciting novel initial results or solutions of practical problems.
Paper/abstract lengths exclude references. All submitted papers and abstracts will undergo a double-blind peer review process by the program committee. We encourage in particular students to submit their work, to engage in an interdisciplinary exchange during the OAGM workshop.
In addition, there will be two awards:
- OCG Best Paper Award for the best full paper
- Best Student Paper Award for the best paper submitted by a student
Further topics of interest include but are not limited to:
Methodological novelty in and applications of
- Pattern recognition
- Machine learning
- Artificial intelligence
- Computer vision
- 3D vision, stereo, and structure from X
- Active learning, interactive machine learning, and human-in-the-loop
- Animal and plant phenotyping
- Embedded and mobile computer vision/machine learning
- Explainability, ethics, and fairness in computer vision/machine learning
- Image denoising, restoration & enhancement
- Image, video, and multimodal retrieval
- (Bio-)Medical image analysis
- Analysis of genomics, next-generation sequencing data
- Linking models across modalities
- Motion and tracking
- Multi- and hyperspectral image analysis
- Object/scene detection, recognition, and categorization
- Pattern analysis (visual and non-visual data)
- Precision agriculture and precision forestry
- Remote sensing and earth observation
- Robot vision and embedded intelligence
- Statistical methods and machine learning
- Video analysis and event recognition
- Vision datasets, benchmarking, and performance evaluation