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Per-frame mAP Prediction for Continuous Performance Monitoring of Object
  Detection During Deployment

Per-frame mAP Prediction for Continuous Performance Monitoring of Object Detection During Deployment

18 September 2020
Q. Rahman
Niko Sünderhauf
Feras Dayoub
ArXivPDFHTML

Papers citing "Per-frame mAP Prediction for Continuous Performance Monitoring of Object Detection During Deployment"

4 / 4 papers shown
Title
Post-hoc Models for Performance Estimation of Machine Learning Inference
Post-hoc Models for Performance Estimation of Machine Learning Inference
Xuechen Zhang
Samet Oymak
Jiasi Chen
UQCV
21
4
0
06 Oct 2021
Semantics for Robotic Mapping, Perception and Interaction: A Survey
Semantics for Robotic Mapping, Perception and Interaction: A Survey
Sourav Garg
Niko Sünderhauf
Feras Dayoub
D. Morrison
Akansel Cosgun
...
Tat-Jun Chin
Ian Reid
Stephen Gould
Peter Corke
Michael Milford
28
115
0
02 Jan 2021
DetNet: A Backbone network for Object Detection
DetNet: A Backbone network for Object Detection
Zeming Li
Chao Peng
Gang Yu
Xiangyu Zhang
Yangdong Deng
Jian Sun
ObjD
88
264
0
17 Apr 2018
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
287
9,167
0
06 Jun 2015
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