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
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

Latest Additions (all)

  1. Item Schreyer, Marco; Schulze, Christian & Borth, Damian: Leaking Sensitive Financial Accounting Data in Plain Sight using Deep Autoencoder Neural Networks. 2021. - AAAI 2021 Workshop on Knowledge Discovery from Unstructured Data in Financial Services. - Virtual. [img]
  2. Item Gierbl, Anita Stefanie; Schreyer, Marco; Leibfried, Peter & Borth, Damian (2020) Künstliche Intelligenz in der Prüfungspraxis - Eine Bestandsaufnahme aktueller Einsatzmöglichkeiten und Herausforderungen. Expert Focus, 2020 (09). 612-617. [img]
  3. Item Steinacker, Léa; Meckel, Miriam; Kostka, Genia & Borth, Damian: Facial Recognition: A cross-national Survey on Public Acceptance, Privacy, and Discrimination. 2020. - International Conference on Machine Learning - Law and ML Workshop. - Vienna. [img]
  4. Item Häfner, Naomi; Gassmann, Oliver & Borth, Damian: Intellectual property protection in the age of self-learning systems: Appropriability issues in artificial intelligence. 2020. - Strategic Management Society Special Conference. - Berkeley, CA.
  5. Item Schreyer, Marco; Sattarov, Timur; Gierbl, Anita Stefanie; Reimer, Bernd & Borth, Damian: Learning Sampling in Financial Statement Audits using Vector Quantised Variational Autoencoder Neural Networks. 2020. - International Conference on Artificial Intelligence in Finance. - New York, NY, USA. [img]
  6. Item van Giffen, Benjamin; Borth, Damian & Brenner, Walter (2020) Management von Künstlicher Intelligenz in Unternehmen. HMD Praxis der Wirtschaftsinformatik, 57 (1). 4-20. ISSN 1436-3011 [img]
  7. Project Borth, Prof. Dr. Damian; Gassmann, Prof. Dr. Oliver; Haefner, Prof. Dr. Naomi & Schürholt, Konstantin (2019) Intellectual Property in the Age of Self-Learning Systems (Neural-IP) [fundamental research project] .
  8. Item Schreyer, Marco; Sattarov, Timur; Reimer, Bernd & Borth, Damian: Adversarial Learning of Deepfakes in Accounting. 2019. - NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy. - Vancouver, British Columbia, Canada. [img]
  9. Item Schreyer, Marco; Sattarov, Timur; Schulze, Christian; Reimer, Bernd & Borth, Damian: Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks. 2019. - 2nd KDD Workshop on Anomaly Detection in Finance, 2019. - Anchorage, Alaska, USA. [img]
  10. Item Patrick, Helber; Benjamin, Bischke; Andreas, Dengel & Damian, Borth (2019) EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12 (7). 2217-2226. [img]
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