Pap-smear Benchmark Data For Pattern Classification

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How researchers see this paper

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Handcrafted vs. non-handcrafted features for computer vision classification (2017, unknown): “ PS (Pap Smear dataset) [48]: includes images of cells used in the diagnosis of cervical cancer.”
DeepPap: Deep Convolutional Networks for Cervical Cell Classification (2017, methodology): “For instance, the Herlev benchmark dataset [17] only contains 917 cells (675 abnormal and 242 normal).”
Local binary patterns variants as texture descriptors for medical image analysis (2010, methodology): “The database collected at the Herlev University Hospital [41] by means of a digital camera and microscope contains 917 samples that belong to seven different classes belonging to two superclasses (normal/abnormal).”
Sipakmed: A New Dataset for Feature and Image Based Classification of Normal and Pathological Cervical Cells in Pap Smear Images (2018, background): “To the best of our knowledge, the only available dataset containing images of single cells is the Harlev dataset [6], which consists of a limited number of images (917).”
COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios (2020, methodology): “They used a dataset composed of 917 images collected at the Herlev University Hospital [33] using digital camera and microscope.”