The concise description of algorithms contains hyperlinks to further information (author, algorithms details, BIB entry, WWW external page).
The algorithm features are: f1 = classification (supervised segmentation), f2 = hiearchy result (manual selection), f3 = known number of regions, f4 = [reserved].
| jolen217's deep_brain_model version 1.0 |
  |
f1: 0 f2: 0 f3: 0 f4: 0 |
Deep Brain Model Deep brain model is an unsupervised segmentation framework with unknown number of classes simulating the deep structure of the primate visual cortex. This model is based on a deep scale space in which a pool of receptive field models in pre-cortical processing and early vision is applied in each scale to produce feature maps. The graph-based image segmentation is then employed to select object boundaries among the edges of superpixels. List of uploaded results for 'deep_brain_model' algorithm
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
