Kai Norman Clasen
Kai Norman Clasen
Doctoral Researcher
Kai Norman Clasen is a Computer Engineer who completed his Master of Science at Technische Universtität Berlin in November 2021. Immediately after his graduation, he began his professional journey at RSiM, where he gained valuable experience developing transformer-based deep learning models for the remote sensing domain before transitioning to BIFOLD in 2023. At BIFOLD, he has shifted his focus towards dataset creation and validation "for remote sensing", with a particular emphasis on reproducibility.
- Machine Learning
- Reproducible Science / Reproducibility
- Data Management
Kai Norman Clasen, Leonard Hackel, Tom Burgert, Gencer Sumbul, Begüm Demir, Volker Markl
reBEN: Refined BigEarthNet Dataset for Remote Sensing Image Analysis
Tom Burgert, Tim Siebert, Kai Norman Clasen, Begüm Demir
A Label Propagation Strategy for CutMix in Multi-Label Remote Sensing Image Classification
Leonard Hackel, Kai Norman Clasen, Begüm Demir
ConfigILM: A general purpose configurable library for combining image and language models for visual question answering
Jakob Hackstein, Gencer Sumbul, Kai Norman Clasen, Begüm Demir
Exploring Masked Autoencoders for Sensor-Agnostic Image Retrieval in Remote Sensing
Marco Corsi, Giorgio Pasquali, Chiara Pratola, Simone Tilia, Sergios-Anestis Kefalidis, Konstantinos Plas, Mariangela Pollali, Eleni Tsalapati, Myrto Tsokanaridou, Manolis Koubarakis, Kai Norman Clasen, Leonard Hackel, Jakob Hackstein, Gencer Sumbul, Begum Demir, Nicolas Longepe´