Chanel-Orderer uses semantic-mask-weighted channel scores to predict the correct R/G/B ordering of a permuted tri-channel image, reporting up to 98.5% accuracy on SiftFlow.
Training stochastic model recognition algo- rithms as networks can lead to maximum mutual information estimation of parameters
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Chanel-Orderer: A Channel-Ordering Predictor for Tri-Channel Natural Images
Chanel-Orderer uses semantic-mask-weighted channel scores to predict the correct R/G/B ordering of a permuted tri-channel image, reporting up to 98.5% accuracy on SiftFlow.