Prof. Dr. Jörn Hees

Contact +49 631 20575 1180 (Kaiserslautern)

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.
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.
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.

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…
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…
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…