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How To Effectively Train An Ensemble Of Faster R-CNN Object Detectors To
  Quantify Uncertainty

How To Effectively Train An Ensemble Of Faster R-CNN Object Detectors To Quantify Uncertainty

7 October 2023
Denis Mbey Akola
Gianni Franchi
    ObjD
    UQCV
ArXivPDFHTML

Papers citing "How To Effectively Train An Ensemble Of Faster R-CNN Object Detectors To Quantify Uncertainty"

3 / 3 papers shown
Title
A Survey of Modern Deep Learning based Object Detection Models
A Survey of Modern Deep Learning based Object Detection Models
Syed Sahil Abbas Zaidi
M. S. Ansari
Asra Aslam
N. Kanwal
M. Asghar
Brian Lee
VLM
ObjD
67
728
0
24 Apr 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
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
296
39,194
0
01 Sep 2014
1