A

Teacher-student collaborative knowledge distillation for image classification

Applied Intelligence, vol. 53, pp. 1997–2009

Abstract

A single model usually cannot learn all the appropriate features with limited data, thus leading to poor performance when test data are used. To improve model performance, we propose a teacher-student collaborative knowledge distillation (TSKD) method based on knowledge distillation and self-distillation. The method consists of two parts: learning in the teacher network and self-teaching in the student network. Learning in the teacher network allows the student network to use knowledge from the teacher network. Self-teaching in the student network is to build a multi-exit network based on self-distillation and provide deep features as supervised information for training. In the inference stage, we use ensembles to vote on the classification results of multiple sub-models in the student network. The experimental results demonstrate the superior performance of our method compared with a traditional knowledge distillation method and a self-distillation-based multi-exit network.

Authors 6

  1. Chongqing Normal University · Chongqing University of Technology

    Affiliation as printed

    College of Computer and Information Science, Chongqing Normal University, Chongqing, 401331, China

    School of Artificial Intelligence, Chongqing University of Technology, Chongqing, 400054, China

  2. Wenjian Gao corresponding

    Chongqing University of Technology

    Affiliation as printed

    School of Artificial Intelligence, Chongqing University of Technology, Chongqing, 400054, China

  3. RWTH Aachen University

    Affiliation as printed

    Computer Science Department, RWTH Aachen University, Aachen, 52074, Germany

  4. Chongqing University of Technology

    Affiliation as printed

    School of Artificial Intelligence, Chongqing University of Technology, Chongqing, 400054, China

  5. Chongqing University of Technology

    Affiliation as printed

    School of Artificial Intelligence, Chongqing University of Technology, Chongqing, 400054, China

  6. Chongqing Normal University

    Affiliation as printed

    College of Computer and Information Science, Chongqing Normal University, Chongqing, 401331, China

Cited by 71 stored of 71

Cited by patents worldwide 1 (Lens.org)

References 37