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Found 3 papers, 1 papers with code
Reducing DNN Labelling Cost using Surprise Adequacy: An Industrial Case Study for Autonomous Driving
The development process in use consists of multiple iterations of data collection, labelling, training, and evaluation.
Guiding Deep Learning System Testing using Surprise Adequacy
Recently, a number of coverage criteria based on neuron activation values have been proposed.
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