Two-stage knowledge transfer framework for image classification

作者：

Highlights：

• We proposed a novel two-stage knowledge transfer method for image classification.

• Decision problem is formulated as a single-teacher single-student (ST-SS) problem.

• A score-based mechanism is used to solve the ST-SS problem.

• We implement two stage ST-SS via sparse and collaborative representations.

• The proposed framework shows effectiveness on different types of image datasets.

摘要

•We proposed a novel two-stage knowledge transfer method for image classification.•Decision problem is formulated as a single-teacher single-student (ST-SS) problem.•A score-based mechanism is used to solve the ST-SS problem.•We implement two stage ST-SS via sparse and collaborative representations.•The proposed framework shows effectiveness on different types of image datasets.

论文关键词：Image classification,Teacher-student model,Two-stage classification,Sparse representation

论文评审过程：Received 8 December 2019, Revised 10 April 2020, Accepted 1 July 2020, Available online 2 July 2020, Version of Record 9 July 2020.

论文官网地址：https://doi.org/10.1016/j.patcog.2020.107529