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researcher

J. Fleischer

4 papers here

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

author position
  • last author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.LG2
same name
  • J. Fleischer — 19 papers, h 23
  • J. Fleischer — 11 papers, h 35
  • J. Fleischer — 5 papers
  • J. Fleischer — 3 papers, h 8
  • J. Fleischer — 1 paper, h 1
  • J. Fleischer — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedA review of systematic selection of clustering algorithms and their evaluation

10 citations · 10 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2021★ 10 cited

A review of systematic selection of clustering algorithms and their evaluation

Marc Wegmann, Domenique Zipperling, Jonas Hillenbrand +1

Data analysis plays an indispensable role for value creation in industry. Cluster analysis in this context is able to explore given datasets with little or no prior knowledge and t…

cs.CV2021

Localization and Tracking of User-Defined Points on Deformable Objects for Robotic Manipulation

Sven Dittus, Benjamin Alt, Andreas Hermann +3

This paper introduces an efficient procedure to localize user-defined points on the surface of deformable objects and track their positions in 3D space over time. To cope with a de…

cs.LG2020

GAN based ball screw drive picture database enlargement for failure classification

Tobias Schlagenhauf, Chenwei Sun, Jürgen Fleischer

The lack of reliable large datasets is one of the biggest difficulties of using modern machine learning methods in the field of failure detection in the manufacturing industry. In…

cs.CV2020

Context-based Image Segment Labeling (CBISL)

Tobias Schlagenhauf, Yefeng Xia, Jürgen Fleischer

Working with images, one often faces problems with incomplete or unclear information. Image inpainting can be used to restore missing image regions but focuses, however, on low-lev…

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