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Teaching with Uncertainty: Unleashing the Potential of Knowledge
  Distillation in Object Detection

Teaching with Uncertainty: Unleashing the Potential of Knowledge Distillation in Object Detection

11 June 2024
Junfei Yi
Jianxu Mao
Tengfei Liu
Mingjie Li
Hanyu Gu
Hui Zhang
Xiaojun Chang
Yaonan Wang
ArXivPDFHTML

Papers citing "Teaching with Uncertainty: Unleashing the Potential of Knowledge Distillation in Object Detection"

3 / 3 papers shown
Title
Avatar Knowledge Distillation: Self-ensemble Teacher Paradigm with
  Uncertainty
Avatar Knowledge Distillation: Self-ensemble Teacher Paradigm with Uncertainty
Yuan Zhang
Weihua Chen
Yichen Lu
Tao Huang
Xiuyu Sun
Jian Cao
44
8
0
04 May 2023
Feature Pyramid Networks for Object Detection
Feature Pyramid Networks for Object Detection
Tsung-Yi Lin
Piotr Dollár
Ross B. Girshick
Kaiming He
Bharath Hariharan
Serge J. Belongie
ObjD
154
3,574
0
09 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
1