The application discloses a boundary sample data enhancement method and device for knowledge
distillation and a computer storage medium. The method comprises the following steps: before knowledge
distillation is performed, the output of a teacher model is used to modify samples in each
original data set along the
decision boundary of the teacher model step by step, and a plurality of boundary samples suitable for knowledge
distillation are expanded. In each iteration, the original sample or each sample modified in the last iteration is used as a basic sample, the approximate tangent plane of the
decision boundary near the sample is calculated by using the output of the teacher model, and the sample is modified along multiple directions on the tangent plane; then, the modified sample is modified to be located near the boundary; finally, a plurality of samples farthest from other basic samples are selected as the result of the modification in the round and the basic samples for the next iteration. The application can meet the demand for data enhancement in current
image classifier knowledge distillation.