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researcher

C. Heipke

3 papers here

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

author position
  • middle author1
  • last author2

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
20192022
most citedA hierarchical deep learning framework for the consistent classification of land use objects in geospatial databases

2 citations · 4 across the 2 of their papers we have counts for

collaborators

3 papers

cs.CV2022★ 2 cited

Learning to Sieve: Prediction of Grading Curves from Images of Concrete Aggregate

Max Coenen, Dries Beyer, Christian Heipke +1

A large component of the building material concrete consists of aggregate with varying particle sizes between 0.125 and 32 mm. Its actual size distribution significantly affects th…

cs.CV2021★ 2 cited

A hierarchical deep learning framework for the consistent classification of land use objects in geospatial databases

Chun Yang, Franz Rottensteiner, Christian Heipke

Land use as contained in geospatial databases constitutes an essential input for different applica-tions such as urban management, regional planning and environmental monitoring. I…

cs.CV2019

CNN-based Cost Volume Analysis as Confidence Measure for Dense Matching

Max Mehltretter, Christian Heipke

Due to its capability to identify erroneous disparity assignments in dense stereo matching, confidence estimation is beneficial for a wide range of applications, e.g. autonomous dr…

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