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(4.05 MB). 2D to 3D body pose estimation for sign language with Deep Learning. . 2020. (2.97 MB)
(2.97 MB). Antipodally Invariant Metrics For Fast Regression-Based Super-Resolution. IEEE Transactions on Image Processing. 2016;25(6):2468. (5.48 MB)
(5.48 MB). Method for upscaling an image and apparatus for upscaling an image. US 20170132759 A1; 2018.
. Manifold Learning for Super Resolution. . [Hannover]: Leibniz Universität Hannover; 2017. (18.6 MB)
(18.6 MB). Bayesian region selection for adaptive dictionary-based Super-Resolution. In British Machine Vision Conference. 2013. (2.59 MB)
(2.59 MB). Fast Super-Resolution via Dense Local Training and Inverse Regressor Search. In Asian Conference in Computer Vision (ACCV). Singapore; 2014. (19.06 MB)
(19.06 MB). PSyCo: Manifold Span Reduction for Super Resolution. In IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, Nevada, USA; 2016. (1.56 MB)
(1.56 MB). Half Hypersphere Confinement for Piecewise Linear Regression. In IEEE Winter Conference on Applications of Computer Vision. Lake Placid, NY, USA; 2016. (7.01 MB)
(7.01 MB). Accelerating Super-Resolution for 4K Upscaling. In IEEE International Conference on Consumer Electronics. Las Vegas, NV, USA; 2015. (1.07 MB)
(1.07 MB). Flexible test-bed for unusual behavior detection. In 6th ACM International Conference on Image and Video Retrieval. 2007. pp. 105–108.
. Characteristic Brain Volumetric Changes in the AD Preclinical Signature. Alzheimer's & Dementia: The Journal of the Alzheimer's Association. 2018;14(7):P1235.
. Magnetic Resonance Imaging as a valuable tool for Alzheimer's disease screening. In Alzheimer’s Association International Conference, London, 2017. 2017.
. Magnetic Resonance Imaging as a valuable tool for Alzheimer's disease screening. Alzheimer's & Dementia: The Journal of the Alzheimer's Association. 2017;13(7):P1245.
. Prediction of amyloid pathology in cognitively unimpaired individuals using voxelwise analysis of longitudinal structural brain MRI. Alzheimer's Research & Therapy. 2019;11(1).
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. Cell Detection with Transformers – A Paradigm Shift from Segmentation to Detection in Digital Pathology. In 21st European Congress on Digital Pathology. 2025. (599.69 KB)
(599.69 KB). Cell-DETR: Efficient cell detection and classification in WSIs with transformers. In Medical Imaging with Deep Learning (MIDL 2024). 2024.
. Self-supervised graph representations of WSIs. In Geometric Deep Learning in Medical Image Analysis. 2022.
. Unsupervised Domain Adaptation for Multi-Stain Cell Detection in Breast Cancer with Transformers. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (DEF-AI-MIA workshop). 2024.
. Layer-Wise Training of Graph Neural Networks With Self-Supervised Learning. IEEE Transactions on Neural Networks and Learning Systems,. 2025;.
. Unsupervised Domain Adaptation for Cell Detection Across Histopathological Stains. In 21st European Congress on Digital Pathology. Barcelona: The European Society of Digital and Integrative Pathology; 2025. (601.11 KB)
(601.11 KB). Feature propagation as self-supervision signals on graphs. Knowledge-Based Systems. 2024;289.
. From pixels to graphs: cell-based digital pathology image analysis. . Signal Theory and Communications. 2025.
. Layer-wise self-supervised learning on graphs. In KDD 2023 Workshop on Deep Learning on Graphs: Methods and Applications (DLG-KDD 2023). Long Beach, USA; 2023.