Abstract. Knowledge Distillation (KD) transfers the knowledge from a cumbersome teacher model to a lightweight student network. Since a single image may ...
Nov 20, 2020 · A simple yet effective feature normalized knowledge distillation which introduces the sample specific correction factor to replace the unified temperature T.
Knowledge Distillation (KD) transfers the knowledge from a cumbersome teacher model to a lightweight student network. Since a single image may reasonably ...
A simple yet effective feature normalized knowledge distillation which introduces the sample specific correction factor to replace the unified temperature T.
Feature Normalized Knowledge Distillation for Image Classification. 7 stars 3 forks Branches Tags Activity.
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The knowledge distillation process involves transferring the knowledge from the teacher to the student model. We employ a combination of soft targets and ...
Jul 7, 2024 · We introduce a novel framework in knowledge distillation, using topological knowledge to generate a compact model for image classification tasks ...
Zero-shot distillation refers to the process of transferring knowledge from a teacher to a student model in a setting where one does not have access to images ...
Jul 26, 2024 · This study systematically investigates the impact of diverse datasets on knowledge distillation in image classification. By varying dataset ...
We propose a knowledge distillation method based on noisy feature reconstruction. Our method is applicable to various tasks, eg, classification and dense ...