Chris Oswald commited on
Commit
2169947
1 Parent(s): 70b4465

updated header

Browse files
Files changed (1) hide show
  1. tutorials/UNet_with_SPIDER.ipynb +2 -2
tutorials/UNet_with_SPIDER.ipynb CHANGED
@@ -24,7 +24,7 @@
24
  "id": "D5gcsQX9XgUZ"
25
  },
26
  "source": [
27
- "## Why U-Net?\n",
28
  "\n",
29
  "U-Net was first introduced in a 2015 paper titled \"[U-Net: Convolutional Networks for Biomedical Image Segmentation](https://arxiv.org/pdf/1505.04597.pdf)\" by Olaf Ronneberger, Philipp Fischer, and Thomas Brox, at the University of Freiburg, Germany. Their paper develops both a model architecture (U-Net) and a training strategy (data augmentation and a weighted loss) that enables more precise image segmentation with relatively few training examples.\n"
30
  ]
@@ -902,7 +902,7 @@
902
  "metadata": {
903
  "colab": {
904
  "base_uri": "https://localhost:8080/",
905
- "height": 461,
906
  "referenced_widgets": [
907
  "b1abebb5f64d4445bfde112a031aeda1",
908
  "098cafccc90849dbbbb7295b393f431a",
 
24
  "id": "D5gcsQX9XgUZ"
25
  },
26
  "source": [
27
+ "## What is U-Net?\n",
28
  "\n",
29
  "U-Net was first introduced in a 2015 paper titled \"[U-Net: Convolutional Networks for Biomedical Image Segmentation](https://arxiv.org/pdf/1505.04597.pdf)\" by Olaf Ronneberger, Philipp Fischer, and Thomas Brox, at the University of Freiburg, Germany. Their paper develops both a model architecture (U-Net) and a training strategy (data augmentation and a weighted loss) that enables more precise image segmentation with relatively few training examples.\n"
30
  ]
 
902
  "metadata": {
903
  "colab": {
904
  "base_uri": "https://localhost:8080/",
905
+ "height": 464,
906
  "referenced_widgets": [
907
  "b1abebb5f64d4445bfde112a031aeda1",
908
  "098cafccc90849dbbbb7295b393f431a",