The Prague Texture Segmentation Datagenerator and Benchmark - Algorithms
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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
BIB
WEB
f1: 0
f2: 0
f3: 0
f4: 0
Nan Zhao:   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
   benchmark label version CS OS US ME NE O C CA CO CC I II EA MS RM CI GCE LCE BCE GBCE BGM SC SSC VD L AVI NVI NMI M ARI JC DC FMI WI WII NBDE
#Colour [large] deep_brain_model 1.0 0.00 0.00 98.05 0.00 1.95 99.84 68.31 10.07 29.79 15.19 70.21 29.23 15.22 -5.31 30.12 18.26 3.74 3.34 79.39 78.99 29.79 29.17 20.82 36.04 26.94 14.42 48.49 1.42 76.73 0.22 20.77 33.93 44.46 20.93 96.66 8.19
Colour [large] Deep Brain Model 38.00 41.53 52.52 4.21 5.46 45.27 99.63 51.84 64.66 72.83 35.34 9.89 58.77 49.29 2.88 61.50 10.61 5.14 45.13 39.65 64.66 60.14 58.32 19.20 62.95 8.48 10.29 65.13 23.02 51.62 49.93 64.37 67.76 55.31 88.07 8.26
Colour [large] Deep Brain Model 38.00 41.53 52.52 4.21 5.46 45.27 99.63 51.84 64.66 72.83 35.34 9.89 58.77 49.29 2.88 61.50 10.61 5.14 45.13 39.65 64.66 60.14 58.32 19.20 62.95 8.48 10.29 65.13 23.02 51.62 49.93 64.37 67.76 55.31 88.07 8.26
BTF wood [exp.] [normal] DBM 17.86 23.80 62.59 8.06 9.49 70.86 90.33 36.39 52.64 55.90 47.36 14.99 44.70 32.19 11.83 47.92 12.73 7.57 58.79 53.63 52.64 48.10 44.76 26.01 53.35 10.01 25.29 50.52 33.07 33.15 36.28 52.24 57.44 44.86 82.16 14.59