Skip to main content Skip to main navigation

Prof. Dr. Jörn Hees

Organizational unit Smart Data & Knowledge Services
Contact +49 631 20575 1180 (Kaiserslautern)

http://www.dfki.uni-kl.de/~hees
Address (Kaiserslautern)

Publications

Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances

Brian Moser; Federico Raue; Stanislav Frolov; Sebastian Palacio; Jörn Hees; Andreas Dengel

In: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Pages 1-21, IEEE, 2/2023.

To the publication

Sequential Spatial Transformer Networks for Salient Object Classification

David Dembinsky; Fatemeh Azimi; Federico Raue; Jörn Hees; Sebastian Palacio; Andreas Dengel

In: Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods. International Conference on Pattern Recognition Applications and Methods (ICPRAM-2023), located at 12th International Conference on Pattern Recognition Applications and Methods, February 22-24, Lissabon, Portugal, scitepress, 2/2023.

To the publication

Cross-Domain Transformation for Outlier Detection on Tabular Datasets

Dayananda Herurkar; Timur Sattarov; Jörn Hees; Sebastian Palacio; Federico Raue; Andreas Dengel

In: IJCNN 2023 : International Joint Conference on Neural Networks. International Joint Conference on Neural Networks (IJCNN-2023), located at IJCNN, June 18-23, Gold Coast Convention and Exhibition Centre, Queensland, Australia, DFKI Research Reports (RR), IEEE Xplore, 2023.

To the publication
All publications

Profile

  • TreeSatAI

    Künstliche Intelligenz mit Erdbeobachtungs- und Multi-Source Geodaten für das Infrastruktur-, Naturschutz und Waldmonitoring

    Remote sensing data from various space missions as well as geodata on the state of the environment are increasingly available free of charge in immense quantities.At the same time, social media…

    TreeSatAI

  • MInD-Phase_1

    Machine Intelligence and Deep Learning

    Ziel des Projekts “Machine Intelligence and Deep Learning” (MInD) ist die Identifikation und Nutzung von Deep Learning Technologien zur sozio-technischen Gestaltung des digitalen Wandels. Dazu sollen…

  • DeFuseNN

    Deep Fusion für Neuronale Netze

    Motivation

    Focused research and development in the field of Deep Learning, especially in recent years, has resulted in a variety of different network types, architectures, modules, training methods…

    DeFuseNN

  • MOM

    Multimedia Opinion Mining

    This project aims to address the challenge of opinion mining of multimedia content from the web. This comprises a large-scale multi-modal analysis of social media streams and their underlying network…

    MOM