DeepLearnPhysics
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+Title: Training Semantic-Segmentation Data Set (v0.1.0)
+Slug: 2018-01-05-TrainingSegmentationData_v0.1.0
+Lang: en
+Date: 2018-01-05
+Category: semantic segmentation
+Tags: public data, semantic segmentation, u-resnet
+Authors: Kazuhiro Terao
+Summary: A demonstration to train U-ResNet (convolutional neural network for semantic segmentation) for track/shower separation using a (practice) public data sample (v0.1.0). I show the network's learning curve as well as visualization of how the network's performance improved during the training on a specific track/shower sample image. This notebook can also serve as a generic example of configuring larcv IO to train a semantic segmentation network.
@@ -15,7 +15,7 @@
 SITEDESCRIPTION = 'description!'
 SITELOGO = 'profile.png'
 SITEURL = GROUPURL + '/Blog'
-#SITEURL = '' # uncomment this line for local dev
+SITEURL = '' # uncomment this line for local dev
 #FAVICON = SITEURL + '/images/favicon.ico'
 
 BROWSER_COLOR='#333'