Daniel Schneider

Daniel Schneider is a Research Fellow at Philipps-Universität Marburg, affiliated with the Department of Distributed Systems within the Faculty of Mathematics and Computer Science. He is part of Prof. Bernd Freisleben's research group, where he began his PhD in 2020.

Education:
Daniel holds a Master of Science (M.Sc.) and is currently pursuing his PhD under Prof. Freisleben's supervision.

Research Interests:
His work focuses on deep neural networks applied to multimedia data analysis, spanning both wildlife monitoring and music information retrieval. In wildlife research, he develops AI-driven systems for analyzing camera trap images to identify European mammals and birds, addressing ecological data challenges. For musicology, he specializes in automating the transcription of historical organ tablature notation into modern formats, preserving cultural heritage through computational methods.

Publications:
His recent papers highlight trends in leveraging deep learning for interdisciplinary applications: from real-time species recognition at the edge (Bird@ Edge) to systems like DeepTab for music notation digitization. These contributions bridge computer science innovations with ecological and cultural preservation domains.

Advising & Grants:
As a PhD student, Daniel is advised by Prof. Freisleben. No grants are explicitly mentioned in the provided texts.

Labs & Teams:
He is a core member of the Distributed Systems and Intelligent Computing research group at Philipps-Universität Marburg.