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Image Classification on SAT-6 (test)

99.84AccuracyDeepSat V2
75.535281.845188.15594.4649Sep 11, 2015May 22, 2016Jan 31, 2017Oct 13, 2017Jun 24, 2018Mar 5, 2019Nov 15, 2019
Updated 8mo ago

Evaluation results

MethodLinks
DeepSat V22019.1199.84
Triplet networks2019.1199.71
SatCNNNormalization=Z-score2019.1199.61
SatCNNNormalization=linear2019.1199.58
D-DSML-CaffeNet2019.1199.42
Contrastive loss2019.1198.55
TradCNNNormalization=Z-score2019.1198.34
MLPNormalization=Z-score2019.1197.46
DCNN2019.1196.04
DeepSat2019.1193.92
DeepSatNeurons per layer=50, Layers=22015.0993.916
DeepSatNeurons per layer=20, Layers=32015.0993.42
DeepSatNeurons per layer=50, Layers=32015.0992.65
DeepSatNeurons per layer=10, Layers=22015.0991.91
DeepSatNeurons per layer=100, Layers=32015.0991.057
DeepSatNeurons per layer=100, Layers=22015.0989.08
DeepSatNeurons per layer=10, Layers=32015.0987.716
DeepSatNeurons per layer=20, Layers=22015.0986.21
CNN2019.1179.1
SDAE2019.1178.43
DBN2019.1176.47