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Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides., , , , , , , , , and 6 other author(s). CoRR, (2019)Learning New Tricks from Old Dogs - Inter-Species, Inter-Tissue Domain Adaptation for Mitotic Figure Assessment., , , , , and . CoRR, (2019)Augmented Mitotic Cell Count using Field Of Interest Proposal., , , and . CoRR, (2018)Augmented Mitotic Cell Count Using Field of Interest Proposal., , , and . Bildverarbeitung für die Medizin, page 321-326. Springer Vieweg, (2019)Fooling the Crowd with Deep Learning-based Methods., , , , , , , , and . CoRR, (2019)Field of Interest Prediction for Computer-Aided Mitotic Count., , , , , , , , , and 2 other author(s). CoRR, (2019)Field Of Interest Proposal for Augmented Mitotic Cell Count: Comparison of two Convolutional Networks., , , and . CoRR, (2018)Field of Interest Proposal for Augmented Mitotic Cell Count: Comparison of Two Convolutional Networks., , , and . BIOIMAGING, page 30-37. SciTePress, (2019)978-989-758-353-7.Pan-Tumor CAnine cuTaneous Cancer Histology (CATCH) Dataset., , , , , , , , and . CoRR, (2022)