HIGHLIGHTS
SUMMARY
The Bayesian neural_network(BNN) method puts the prior value above the network weight and estimates the prediction uncertainty by approximating the moment of the posterior prediction distribution. In the cross-country environment, "Two models + one frame" is 10.6% higher than "One model + one frame" because during the mixed training of "junctions" and "non-junctions", the model is overfitted to "non-junctions", but the learning ability of the model to the "junctions" sample is improved after separate training. The authors conduct comparative experiments on the three schemes of "One model + one frame", "Two models . . .
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