Profile Page Prof. Dr. Damian Borth

Profile Picture
Name Damian Borth
Title Prof. Dr.
Function
Institute/School ICS - Institute of Computer Science
Address School of Computer Science (SCS) - Institute of Computer Science (ICS-HSG)
Büro 61-510
Rosenbergstrasse 30
9000 St. Gallen
Schweiz
Email address damian.borth@unisg.ch
Phone +41 71 224 26 27
Homepage https://ics.unisg.ch/chair-aiml-borth/
Twitter https://twitter.com/damianborth
Google Scholar https://scholar.google.de/citations?user=J-8Z038AAAAJ
Main Focuses Maschinelles Lernen, Deep Learning, Künstliche Intelligenz, Satelliten Bildanalyse
Education
Teaching Activities
Affiliations
Awards
Additional Information

Latest Additions (all)

  1. Item Schreyer, Marco; Hemati, Hamed; Borth, Damian & Vasarhelyi, Miklos A.: Federated Continual Learning to Detect Accounting Anomalies in Financial Auditing. 2022. - Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022). - New Orleans, LA, USA. [img]
  2. Item Schreyer, Marco; Sattarov, Timur & Borth, Damian: Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits. 2022. - 3rd ACM International Conference on Artificial Intelligence in Finance (ICAIF). - New York City, USA. [img]
  3. Item Schürholt, Konstantin; Knyazev, Boris; Giro-i-Nieto, Xavier & Borth, Damian: Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights. 2022. - Conference on Neural Information Processing Systems. - New Orleans. [img]
  4. Item Schürholt, Konstantin; Taskiran, Diyar; Knyazev, Boris; Giro-i-Nieto, Xavier & Borth, Damian: Model Zoos: A Dataset of Diverse Populations of Neural Network Models. 2022. - 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks.. [img]
  5. Item Hanna, Joëlle; Mommert, Michael & Borth, Damian: Estimation of Power Generation and CO2 Emissions Using Satellite Imagery. 2022. - AI4EO Symposium. - Munich. [img]
  6. Item Scheibenreif, Linus Mathias; Hanna, Joëlle; Mommert, Michael & Borth, Damian: Multi-modal Self-supervised Learning for Earth Observation. [Conference or Workshop Item] [img]
  7. Item Mommert, Michael; Blattner, Moritz; Eicher, Leonardo & Borth, Damian: Quantifying Traffic with Deep Learning from Earth Observation Data. [Conference or Workshop Item] [img]
  8. Item Eicher, Leonardo; Mommert, Michael & Borth, Damian: Traffic Noise Estimation from Satellite Imagery with Deep Learning. 2022. - IEEE Geoscience and Remote Sensing Symposium 2022. - Kuala Lumpur, Malaysia. [img]
  9. Item Hanna, Joëlle; Scheibenreif, Linus Mathias; Mommert, Michael & Borth, Damian: A Multimodal Approach for Event Detection: Study of UK Lockdowns in the Year 2020. 2022. - IEEE Geoscience and Remote Sensing Symposium 2022. - Kuala Lumpur, Malaysia. [img]
  10. Item Scheibenreif, Linus Mathias; Hanna, Joëlle; Mommert, Michael & Borth, Damian: Self-supervised Vision Transformers for Land-cover Segmentation and Classification. 2022. [img]
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