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2019

Fooling the Crowd with Deep Learning-based Methods

Marzahl, Christian, Aubreville, Marc, Bertram, Christof A. et al.

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Modern, state-of-the-art deep learning approaches yield human like performance in numerous object detection and classification tasks.

The foundation for their success is the availability of training datasets of substantially high quantity, which are expensive to create, especially in the field of medical imaging.
Recently, crowdsourcing has been applied to create large datasets for a broad range of disciplines.
This study aims to explore the challenges and opportunities of crowd-algorithm collaboration for the object detection task of grading cytology whole slide images.

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Original
Labelbox. Labelbox; 2019 · 1912
Earlier work this paper cites.
Occult pulmonary haemorrhage in leukaemia
Golde DW, Drew WL, Klein HZ, et al · 1975
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Alveolar macrophage graded hemosiderin score from bronchoalveolar lavage in horses with exercise-induced pulmonary hemorrhage and controls
Doucet MY, Viel L · 2002
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Then

A survey of crowdsourcing in medical image analysis
Ørting S, Doyle A, van Hilten MHA, et al · 2019
Closest in time.
Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides
Marzahl C, Aubreville M, Bertram CA, et al · 2019
Closest in time.

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