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gptkbp:instanceOf
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gptkb:model
|
|
gptkbp:application
|
biomedical image segmentation
|
|
gptkbp:architecture
|
gptkb:convolutional_neural_network
|
|
gptkbp:citation
|
over 30,000
|
|
gptkbp:hasDecoder
|
yes
|
|
gptkbp:hasEncoder
|
yes
|
|
gptkbp:hasSkipConnections
|
yes
|
|
gptkbp:influenced
|
gptkb:3D_U-Net
gptkb:Attention_U-Net
gptkb:UNet++
|
|
gptkbp:influencedBy
|
gptkb:fully_convolutional_networks
|
|
gptkbp:input
|
images
|
|
gptkbp:introduced
|
gptkb:Thomas_Brox
gptkb:Olaf_Ronneberger
gptkb:Philipp_Fischer
|
|
gptkbp:introducedIn
|
2015
|
|
gptkbp:notableFor
|
U-shaped architecture
|
|
gptkbp:notablePublication
|
gptkb:U-Net:_Convolutional_Networks_for_Biomedical_Image_Segmentation
|
|
gptkbp:openSource
|
gptkb:TensorFlow
gptkb:Keras
gptkb:PyTorch
|
|
gptkbp:output
|
segmentation maps
|
|
gptkbp:publishedIn
|
gptkb:MICCAI_2015
|
|
gptkbp:trainer
|
gptkb:ISBI_cell_tracking_challenge
|
|
gptkbp:usedFor
|
image segmentation
|
|
gptkbp:bfsParent
|
gptkb:Mirror_Networking
|
|
gptkbp:bfsLayer
|
7
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
UNet
|