Dr. Sören Klemm

2020

• Huesmann, K, Klemm, S, Linsen, L, und Risse, B. 2020. Exploiting the Full Capacity of Deep Neural Networks while Avoiding Overfitting by Targeted Sparsity Regularization arXiv e-print:2002.09237: CoRR.
• Klemm, S, Rexeisen, R, Stummer, W, Jiang, X, und Holling, M. 2020. „A video processing pipeline for intraoperative analysis of cerebral blood flow.“ Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization 8 (4): 356–366. doi: 10.1080/21681163.2018.1559771.

2019

• Hamid, S, Derstroff, A, Klemm, S, Ngo, Q.Q., Jiang, X, und Linsen, L. 2019. „Visual ensemble analysis to study the influence of hyper-parameters on training deep neural networks.“ In Machine Learning Methods in Visualisation for Big Data, herausgegeben von Daniel and Nabney Archambault und Jaakko Ian and Peltonen. Eurographics Association. doi: 10.2312/mlvis.20191160.
• Klemm, S, Ortkemper, RD, und Jiang, X. 2019. „Deploying Deep Learning into practice: A case study on fundus segmentation.“ Beitrag präsentiert auf der Proc. of 23rd Conference in Medical Imaging, Understanding and Analysis, Liverpool, UK

2018

• Klemm, S, Scherzinger, A, Drees, D, und Jiang, X. 2018. Barista - a graphical tool for designing and training deep neural networks arXiv e-print:1802.04626: CoRR.
• Klemm, S, Jiang, X, und Risse, B. 2018. „Deep distance transform to segment visually indistinguishable merged objects.“ Beitrag präsentiert auf der Proc. of 40th German Conference on Pattern Recognition (GCPR), Stuttgart

2017

• Scherzinger, A, Klemm, S, Berh, D, und Jiang, X. 2017. „CNN-based background subtraction for long-term in-vial FIM imaging.“ Beitrag präsentiert auf der Proc. of 17th Int. Conf. on Computer Analysis of Images and Patterns (CAIP), Ystad, Sweden

2015

• Klemm, S, Andreu, Y, Henriquez, P, und Matuszewski, B. 2015. „Robust Face Recognition using Key-point Descriptors.“ In VISAPP 2015 - Proceedings of the 10th International Conference on Computer Vision Theory and Applications, Volume 2, Berlin, Germany, 11-14 March, 2015, herausgegeben von José Braz, Sebastiano Battiato und Francisco H. Imai. SciTePress.