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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

ETRI Journal (ETRI J.), 2019
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"

9 / 9 papers shown
Title
Constricting Normal Latent Space for Anomaly Detection with Normal-only
  Training Data
Constricting Normal Latent Space for Anomaly Detection with Normal-only Training Data
Marcella Astrid
Muhammad Zaigham Zaheer
Seung-Ik Lee
UQCV
146
1
0
24 Mar 2024
Excision And Recovery: Visual Defect Obfuscation Based Self-Supervised
  Anomaly Detection Strategy
Excision And Recovery: Visual Defect Obfuscation Based Self-Supervised Anomaly Detection Strategy
Yeonghyeon Park
Sungho Kang
Myung Jin Kim
Yeonho Lee
Hyeong Seok Kim
Juneho Yi
AAML
322
4
0
06 Oct 2023
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 AmplificationIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
Yeonghyeon Park
Sungho Kang
Myung Jin Kim
Hyeonho Jeong
H. Park
Hyeong Seok Kim
Juneho Yi
219
6
0
28 Aug 2023
PseudoBound: Limiting the anomaly reconstruction capability of one-class
  classifiers using pseudo anomalies
PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomaliesNeurocomputing (Neurocomputing), 2023
Marcella Astrid
M. Zaheer
Seung-Ik Lee
193
25
0
19 Mar 2023
Concise Logarithmic Loss Function for Robust Training of Anomaly
  Detection Model
Concise Logarithmic Loss Function for Robust Training of Anomaly Detection Model
Yeonghyeon Park
AAML
101
4
0
15 Jan 2022
Latent Vector Expansion using Autoencoder for Anomaly Detection
Latent Vector Expansion using Autoencoder for Anomaly Detection
U. Gim
Yeonghyeon Park
DRL
78
0
0
05 Jan 2022
Efficient Non-Compression Auto-Encoder for Driving Noise-based Road
  Surface Anomaly Detection
Efficient Non-Compression Auto-Encoder for Driving Noise-based Road Surface Anomaly DetectionIEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING (IEEJ Trans. Electr. Electron. Eng.), 2021
Yeonghyeon Park
JongHee Jung
330
4
0
22 Nov 2021
Anomaly Detection Based on Multiple-Hypothesis Autoencoder
Anomaly Detection Based on Multiple-Hypothesis Autoencoder
Joonsung Lee
Yeonghyeon Park
84
1
0
07 Jul 2021
Non-Compression Auto-Encoder for Detecting Road Surface Abnormality via
  Vehicle Driving Noise
Non-Compression Auto-Encoder for Detecting Road Surface Abnormality via Vehicle Driving Noise
Yeonghyeon Park
JongHee Jung
132
2
0
24 Mar 2021
1