activity
20192021
most citedFooling the Crowd with Deep Learning-based Methods

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

collaborators

5 papers

cs.HC2021

Inter-Species Cell Detection: Datasets on pulmonary hemosiderophages in equine, human and feline specimens

Christian Marzahl, Jenny Hill, Jason Stayt +9

Pulmonary hemorrhage (P-Hem) occurs among multiple species and can have various causes. Cytology of bronchoalveolarlavage fluid (BALF) using a 5-tier scoring system of alveolar mac…

eess.IV20211 cited

Learning to be EXACT, Cell Detection for Asthma on Partially Annotated Whole Slide Images

Christian Marzahl, Christof A. Bertram, Frauke Wilm +6

Asthma is a chronic inflammatory disorder of the lower respiratory tract and naturally occurs in humans and animals including horses. The annotation of an asthma microscopy whole s…

cs.HC2020

Are fast labeling methods reliable? A case study of computer-aided expert annotations on microscopy slides

Christian Marzahl, Christof A. Bertram, Marc Aubreville +12

Deep-learning-based pipelines have shown the potential to revolutionalize microscopy image diagnostics by providing visual augmentations to a trained pathology expert. However, to…

cs.HC20193 cited

Fooling the Crowd with Deep Learning-based Methods

Christian Marzahl, Marc Aubreville, Christof A. Bertram +6

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 availa…

eess.IV2019

Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides

Christian Marzahl, Marc Aubreville, Christof A. Bertram +13

Purpose: Exercise-induced pulmonary hemorrhage (EIPH) is a common syndrome in sport horses with negative impact on performance. Cytology of bronchoalveolar lavage fluid by use of a…