7 citations · 15 across the 18 of their papers we have counts for
5 papers · 1 filter
Noise Reduction and Driving Event Extraction Method for Performance Improvement on Driving Noise-based Surface Anomaly Detection
YeongHyeon Park, JoonSung Lee, Myung Jin Kim +1
Foreign substances on the road surface, such as rainwater or black ice, reduce the friction between the tire and the surface. The above situation will reduce the braking performanc…
Efficient Non-Compression Auto-Encoder for Driving Noise-based Road Surface Anomaly Detection
YeongHyeon Park, JongHee Jung
Wet weather makes water film over the road and that film causes lower friction between tire and road surface. When a vehicle passes the low-friction road, the accident can occur up…
Anomaly Detection Based on Multiple-Hypothesis Autoencoder
JoonSung Lee, YeongHyeon Park
Recently Autoencoder(AE) based models are widely used in the field of anomaly detection. A model trained with normal data generates a larger restoration error for abnormal data. Wh…
Self-Weighted Ensemble Method to Adjust the Influence of Individual Models based on Reliability
YeongHyeon Park, JoonSung Lee, Wonseok Park
Image classification technology and performance based on Deep Learning have already achieved high standards. Nevertheless, many efforts have conducted to improve the stability of c…
Non-Compression Auto-Encoder for Detecting Road Surface Abnormality via Vehicle Driving Noise
YeongHyeon Park, JongHee Jung
Road accident can be triggered by wet road because it decreases skid resistance. To prevent the road accident, detecting road surface abnomality is highly useful. In this paper, we…