Dataset Open Access

Rotation Equivariant CNNs for Digital Pathology

B. S. Veeling, J. Linmans, J. Winkens, T. Cohen, M. Welling


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{
  "DOI": "10.1007/978-3-030-00934-2_24", 
  "author": [
    {
      "family": "B. S. Veeling, J. Linmans, J. Winkens, T. Cohen, M. Welling"
    }
  ], 
  "issued": {
    "date-parts": [
      [
        2018, 
        9, 
        26
      ]
    ]
  }, 
  "abstract": "<p>The PatchCamelyon benchmark is a new and challenging image classification dataset. It consists of 327.680 color images (96 x 96px) extracted from histopathologic scans of lymph node sections. Each image is annoted with a binary label indicating presence of metastatic tissue. PCam provides a new benchmark for machine learning models: bigger than CIFAR10, smaller than imagenet, trainable on a single GPU.</p>", 
  "title": "Rotation Equivariant CNNs for Digital Pathology", 
  "type": "dataset", 
  "id": "2546921"
}
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