Statements (23)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:model
semantic segmentation model |
| gptkbp:appliesTo |
robotics
autonomous driving medical image analysis |
| gptkbp:architecture |
encoder-decoder
|
| gptkbp:basedOn |
gptkb:SegNet
|
| gptkbp:designedFor |
semantic segmentation
|
| gptkbp:estimatedCost |
model uncertainty
|
| https://www.w3.org/2000/01/rdf-schema#label |
Bayesian SegNet
|
| gptkbp:implementedIn |
gptkb:Python
gptkb:TensorFlow gptkb:Keras |
| gptkbp:improves |
uncertainty estimation in segmentation
|
| gptkbp:proposedBy |
gptkb:Roberto_Cipolla
gptkb:Alex_Kendall gptkb:Vijay_Badrinarayanan |
| gptkbp:publicationYear |
2017
|
| gptkbp:publishedIn |
Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding
|
| gptkbp:uses |
Bayesian inference
Monte Carlo dropout |
| gptkbp:bfsParent |
gptkb:Dr._Alex_Kendall
|
| gptkbp:bfsLayer |
8
|