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No Need to Sacrifice Data Quality for Quantity: Crowd-Informed Machine
  Annotation for Cost-Effective Understanding of Visual Data

No Need to Sacrifice Data Quality for Quantity: Crowd-Informed Machine Annotation for Cost-Effective Understanding of Visual Data

19 August 2024
Christopher Klugmann
Rafid Mahmood
Guruprasad Hegde
Amit Kale
Daniel Kondermann
ArXiv (abs)PDFHTML

Papers citing "No Need to Sacrifice Data Quality for Quantity: Crowd-Informed Machine Annotation for Cost-Effective Understanding of Visual Data"

3 / 3 papers shown
Title
Quantifying Ambiguity in Categorical Annotations: A Measure and Statistical Inference Framework
Quantifying Ambiguity in Categorical Annotations: A Measure and Statistical Inference Framework
Christopher Klugmann
Daniel Kondermann
UD
179
0
0
05 Oct 2025
Minority Reports: Balancing Cost and Quality in Ground Truth Data Annotation
Minority Reports: Balancing Cost and Quality in Ground Truth Data Annotation
Hsuan Wei Liao
Christopher Klugmann
Daniel Kondermann
Rafid Mahmood
171
0
0
12 Apr 2025
Ambiguous Annotations: When is a Pedestrian not a Pedestrian?
Ambiguous Annotations: When is a Pedestrian not a Pedestrian?
Luisa Schwirten
Jannes Scholz
Daniel Kondermann
Janis Keuper
149
4
0
14 May 2024
1