Search Results for author: Josef Scharinger

Found 9 papers, 5 papers with code

Nuclear Pleomorphism in Canine Cutaneous Mast Cell Tumors: Comparison of Reproducibility and Prognostic Relevance between Estimates, Manual Morphometry and Algorithmic Morphometry

no code implementations26 Sep 2023 Andreas Haghofer, Eda Parlak, Alexander Bartel, Taryn A. Donovan, Charles-Antoine Assenmacher, Pompei Bolfa, Michael J. Dark, Andrea Fuchs-Baumgartinger, Andrea Klang, Kathrin Jäger, Robert Klopfleisch, Sophie Merz, Barbara Richter, F. Yvonne Schulman, Hannah Janout, Jonathan Ganz, Josef Scharinger, Marc Aubreville, Stephan M. Winkler, Matti Kiupel, Christof A. Bertram

We assessed the following nuclear evaluation methods for measurement accuracy, reproducibility, and prognostic utility: 1) anisokaryosis (karyomegaly) estimates by 11 pathologists; 2) gold standard manual morphometry of at least 100 nuclei; 3) practicable manual morphometry with stratified sampling of 12 nuclei by 9 pathologists; and 4) automated morphometry using a deep learning-based segmentation algorithm.

Specificity

BlendTorch: A Real-Time, Adaptive Domain Randomization Library

1 code implementation6 Oct 2020 Christoph Heindl, Lukas Brunner, Sebastian Zambal, Josef Scharinger

Solving complex computer vision tasks by deep learning techniques relies on large amounts of (supervised) image data, typically unavailable in industrial environments.

object-detection Object Detection

End-to-End Defect Detection in Automated Fiber Placement Based on Artificially Generated Data

no code implementations11 Oct 2019 Sebastian Zambal, Christoph Heindl, Christian Eitzinger, Josef Scharinger

This leads to an appealing method that scales well with new defect types and measurement devices and requires little real world data for training.

Defect Detection Image Segmentation +2

Metric Pose Estimation for Human-Machine Interaction Using Monocular Vision

no code implementations8 Oct 2019 Christoph Heindl, Markus Ikeda, Gernot Stübl, Andreas Pichler, Josef Scharinger

The rapid growth of collaborative robotics in production requires new automation technologies that take human and machine equally into account.

Pose Estimation

Enhanced Human-Machine Interaction by Combining Proximity Sensing with Global Perception

1 code implementation6 Oct 2019 Christoph Heindl, Markus Ikeda, Gernot Stübl, Andreas Pichler, Josef Scharinger

The raise of collaborative robotics has led to wide range of sensor technologies to detect human-machine interactions: at short distances, proximity sensors detect nontactile gestures virtually occlusion-free, while at medium distances, active depth sensors are frequently used to infer human intentions.

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