现代信息科技2024，Vol.8Issue(16)：49-52,59,5.DOI:10.19850/j.cnki.2096-4706.2024.16.011
基于多分类器分级蒸馏的长尾视觉识别方法
Long-tailed Visual Recognition Method Based on Multi-classifier Graded Distillation
巩炫瑾1
作者信息
- 1. 福建理工大学 计算机科学与数学学院,福建 福州 350118
- 折叠
摘要
Abstract
In order to enhance model performance in the long-tailed visual recognition domain,this paper proposes a multi-classifier graded distillation framework.The framework comprises rotation self-supervised pre-training and multi-classifier distillation.Rotation self-supervised pre-training treats each image equally by predicting image rotations,and mitigates the impact of long-tailed labels on the model.Multi-classifier systematically distills the knowledge from the teacher model to the student model through three specifically optimized classifiers.Extensive experiment results are conducted on open-source long-tailed image recognition datasets,and comparisons are made with existing methods.The experimental results demonstrate that the proposed method achieves notable improvements in long-tailed image visual recognition.关键词
知识蒸馏/长尾分布/图像识别/深度学习模型Key words
knowledge distillation/long-tailed distribution/image recognition/Deep Learning model分类
信息技术与安全科学引用本文复制引用
巩炫瑾..基于多分类器分级蒸馏的长尾视觉识别方法[J].现代信息科技,2024,8(16):49-52,59,5.
