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researcher

Tobias Schack

3 papers hereh-index 6137 citations23 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV3

identity via Semantic Scholar / OpenAlex

activity
20212024
most citedConsInstancy: Learning Instance Representations for Semi-Supervised Panoptic Segmentation of Concrete Aggregate Particles

4 citations · 9 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CV2024★ 1 cited

Image-based Deep Learning for the time-dependent prediction of fresh concrete properties

Max Meyer, Amadeus Langer, Max Mehltretter +5

Increasing the degree of digitisation and automation in the concrete production process can play a crucial role in reducing the CO2​ emissions that are associated with the produc…

cs.CV2022★ 4 cited

ConsInstancy: Learning Instance Representations for Semi-Supervised Panoptic Segmentation of Concrete Aggregate Particles

Max Coenen, Tobias Schack, Dries Beyer +2

We present a semi-supervised method for panoptic segmentation based on ConsInstancy regularisation, a novel strategy for semi-supervised learning. It leverages completely unlabelle…

cs.CV2021★ 4 cited

Semi-Supervised Segmentation of Concrete Aggregate Using Consensus Regularisation and Prior Guidance

Max Coenen, Tobias Schack, Dries Beyer +2

In order to leverage and profit from unlabelled data, semi-supervised frameworks for semantic segmentation based on consistency training have been proven to be powerful tools to si…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.