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DEAL: Deep Evidential Active Learning for Image Classification

DEAL: Deep Evidential Active Learning for Image Classification

22 July 2020
Patrick Hemmer
Niklas Kühl
Jakob Schöffer
ArXivPDFHTML

Papers citing "DEAL: Deep Evidential Active Learning for Image Classification"

5 / 5 papers shown
Title
Factors that influence the adoption of human-AI collaboration in
  clinical decision-making
Factors that influence the adoption of human-AI collaboration in clinical decision-making
Patrick Hemmer
Max Schemmer
Lara Riefle
Nico Rosellen
Michael Vossing
Niklas Kühl
26
11
0
19 Apr 2022
Utilizing Active Machine Learning for Quality Assurance: A Case Study of
  Virtual Car Renderings in the Automotive Industry
Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry
Patrick Hemmer
Niklas Kühl
Jakob Schöffer
13
4
0
18 Oct 2021
Detecting Concept Drift With Neural Network Model Uncertainty
Detecting Concept Drift With Neural Network Model Uncertainty
Lucas Baier
Tim Schlör
Jakob Schöffer
Niklas Kühl
11
27
0
05 Jul 2021
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
285
9,136
0
06 Jun 2015
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
266
7,634
0
03 Jul 2012
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