The Prague Texture Segmentation Datagenerator and Benchmark - Algorithms
optimized
for

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].
huangyuan's
EWT-FCNT
BIB
DOC
f1: 1
f2: 0
f3: 0
f4: 0
Yuan Huang, Fugen Zhou, Jérôme Gilles:   Empirical curvelet based Fully Convolutional Network for supervised texture image segmentation

List of uploaded results for 'EWT-FCNT' 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 [normal] CL EWT-FCNT 98.45 0.00 0.00 0.37 0.46 0.93 1.05 97.67 98.78 98.81 1.22 0.25 98.76 98.17 0.24 98.78 2.23 1.68 2.88 2.33 98.78 97.69 97.67 1.21 97.86 1.02 3.33 96.32 0.74 97.61 96.31 98.09 98.09 98.14 98.04 0.60
#Colour [normal] CL EWT-FCNT-NR 98.11 0.00 0.00 0.49 0.46 1.16 1.56 97.01 98.43 98.46 1.57 0.33 98.40 97.65 0.28 98.42 2.85 2.23 3.63 3.02 98.43 97.08 97.01 1.57 97.28 1.31 4.24 95.30 0.99 96.84 95.17 97.47 97.48 97.53 97.43 1.71