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Anomaly Detection in Particulate Matter Sensor using Hypothesis Pruning
  Generative Adversarial Network
v1v2 (latest)

Anomaly Detection in Particulate Matter Sensor using Hypothesis Pruning Generative Adversarial Network

2 December 2019
Yeonghyeon Park
Wonseok Park
Yeong Beom Kim
ArXiv (abs)PDFHTML

Papers citing "Anomaly Detection in Particulate Matter Sensor using Hypothesis Pruning Generative Adversarial Network"

3 / 3 papers shown
Title
Neural Network Training Strategy to Enhance Anomaly Detection
  Performance: A Perspective on Reconstruction Loss Amplification
Neural Network Training Strategy to Enhance Anomaly Detection Performance: A Perspective on Reconstruction Loss Amplification
Yeonghyeon Park
Sungho Kang
Myung Jin Kim
Hyeonho Jeong
H. Park
Hyeong Seok Kim
Juneho Yi
69
4
0
28 Aug 2023
Latent Vector Expansion using Autoencoder for Anomaly Detection
Latent Vector Expansion using Autoencoder for Anomaly Detection
U. Gim
Yeonghyeon Park
DRL
25
0
0
05 Jan 2022
Anomaly Detection Based on Multiple-Hypothesis Autoencoder
Anomaly Detection Based on Multiple-Hypothesis Autoencoder
Joonsung Lee
Yeonghyeon Park
23
0
0
07 Jul 2021
1