468 citations · 483 across the 6 of their papers we have counts for
6 papers
Frequency of Interest-based Noise Attenuation Method to Improve Anomaly Detection Performance
YeongHyeon Park, Myung Jin Kim, Won Seok Park
Accurately extracting driving events is the way to maximize computational efficiency and anomaly detection performance in the tire frictional nose-based anomaly detection task. Thi…
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…
Sensor Adversarial Traits: Analyzing Robustness of 3D Object Detection Sensor Fusion Models
Won Park, Nan Liu, Qi Alfred Chen +1
A critical aspect of autonomous vehicles (AVs) is the object detection stage, which is increasingly being performed with sensor fusion models: multimodal 3D object detection models…
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…
Anomaly Detection in Particulate Matter Sensor using Hypothesis Pruning Generative Adversarial Network
YeongHyeon Park, Won Seok Park, Yeong Beom Kim
World Health Organization (WHO) provides the guideline for managing the Particulate Matter (PM) level because when the PM level is higher, it threats the human health. For managing…
Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving
Yulong Cao, Chaowei Xiao, Benjamin Cyr +6
In Autonomous Vehicles (AVs), one fundamental pillar is perception, which leverages sensors like cameras and LiDARs (Light Detection and Ranging) to understand the driving environm…