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Confidence Calibration for Convolutional Neural Networks Using
  Structured Dropout

Confidence Calibration for Convolutional Neural Networks Using Structured Dropout

23 June 2019
Zhilu Zhang
Adrian Dalca
M. Sabuncu
    UQCVBDL
ArXiv (abs)PDFHTML

Papers citing "Confidence Calibration for Convolutional Neural Networks Using Structured Dropout"

14 / 14 papers shown
Title
Hardware-Aware Neural Dropout Search for Reliable Uncertainty Prediction
  on FPGA
Hardware-Aware Neural Dropout Search for Reliable Uncertainty Prediction on FPGA
Zehuan Zhang
Hongxiang Fan
Hao Mark Chen
Lukasz Dudziak
Wayne Luk
BDL
70
0
0
23 Jun 2024
Multiclass Confidence and Localization Calibration for Object Detection
Multiclass Confidence and Localization Calibration for Object Detection
Bimsara Pathiraja
Malitha Gunawardhana
M. H. Khan
UQCV
95
15
0
14 Jun 2023
A Unified Benchmark for the Unknown Detection Capability of Deep Neural
  Networks
A Unified Benchmark for the Unknown Detection Capability of Deep Neural Networks
Jihyo Kim
Jiin Koo
Sangheum Hwang
UQCV
81
20
0
01 Dec 2021
The Devil is in the Margin: Margin-based Label Smoothing for Network
  Calibration
The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration
Bingyuan Liu
Ismail Ben Ayed
Adrian Galdran
Jose Dolz
UQCV
109
72
0
30 Nov 2021
Marginally calibrated response distributions for end-to-end learning in
  autonomous driving
Marginally calibrated response distributions for end-to-end learning in autonomous driving
Clara Hoffmann
Nadja Klein
87
2
0
03 Oct 2021
Learning from Matured Dumb Teacher for Fine Generalization
Learning from Matured Dumb Teacher for Fine Generalization
Heeseung Jung
Kangil Kim
Hoyong Kim
Jong-Hun Shin
73
2
0
12 Aug 2021
A Survey of Uncertainty in Deep Neural Networks
A Survey of Uncertainty in Deep Neural Networks
J. Gawlikowski
Cedrique Rovile Njieutcheu Tassi
Mohsin Ali
Jongseo Lee
Matthias Humt
...
R. Roscher
Muhammad Shahzad
Wen Yang
R. Bamler
Xiaoxiang Zhu
BDLUQCVOOD
242
1,174
0
07 Jul 2021
Taxonomy of Machine Learning Safety: A Survey and Primer
Taxonomy of Machine Learning Safety: A Survey and Primer
Sina Mohseni
Haotao Wang
Zhiding Yu
Chaowei Xiao
Zhangyang Wang
J. Yadawa
91
32
0
09 Jun 2021
Ex uno plures: Splitting One Model into an Ensemble of Subnetworks
Ex uno plures: Splitting One Model into an Ensemble of Subnetworks
Zhilu Zhang
Vianne R. Gao
M. Sabuncu
UQCV
96
6
0
09 Jun 2021
Learning to Cascade: Confidence Calibration for Improving the Accuracy
  and Computational Cost of Cascade Inference Systems
Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems
Shohei Enomoto
Takeharu Eda
UQCV
82
17
0
15 Apr 2021
Ensembling Low Precision Models for Binary Biomedical Image Segmentation
Ensembling Low Precision Models for Binary Biomedical Image Segmentation
Tianyu Ma
Hang Zhang
Hanley Ong
Amar Vora
Thanh D. Nguyen
Ajay Gupta
Yi Wang
M. Sabuncu
UQCV
41
13
0
16 Oct 2020
Intelligence plays dice: Stochasticity is essential for machine learning
Intelligence plays dice: Stochasticity is essential for machine learning
M. Sabuncu
127
6
0
17 Aug 2020
Confidence-Aware Learning for Deep Neural Networks
Confidence-Aware Learning for Deep Neural Networks
J. Moon
Jihyo Kim
Younghak Shin
Sangheum Hwang
UQCV
99
150
0
03 Jul 2020
DropCluster: A structured dropout for convolutional networks
DropCluster: A structured dropout for convolutional networks
Liyang Chen
P. Gautier
Sergul Aydore
47
11
0
07 Feb 2020
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