In ImageNet classification papers top-1 and top-5 error rates are important units for measuring the success of some solutions, but what are those error rates?
In ImageNet Classification with Deep Convolutional Neural Networks by Krizhevsky et al. every solution based on one single CNN (page 7) has no top-5 error rates while the ones with 5 and 7 CNNs have (and also the error rate for 7 CNNs are better than for 5 CNNs).
Does this mean top-1 error rate is the best single error rate for one single CNN?
Is the top-5 error rate simply the accumulated error rate of five CNNs?