2 citations · 3 across the 5 of their papers we have counts for
5 papers
Feature Attenuation of Defective Representation Can Resolve Incomplete Masking on Anomaly Detection
YeongHyeon Park, Sungho Kang, Myung Jin Kim +2
In unsupervised anomaly detection (UAD) research, while state-of-the-art models have reached a saturation point with extensive studies on public benchmark datasets, they adopt larg…
Excision And Recovery: Visual Defect Obfuscation Based Self-Supervised Anomaly Detection Strategy
YeongHyeon Park, Sungho Kang, Myung Jin Kim +3
Due to scarcity of anomaly situations in the early manufacturing stage, an unsupervised anomaly detection (UAD) approach is widely adopted which only uses normal samples for traini…
Neural Network Training Strategy to Enhance Anomaly Detection Performance: A Perspective on Reconstruction Loss Amplification
YeongHyeon Park, Sungho Kang, Myung Jin Kim +4
Unsupervised anomaly detection (UAD) is a widely adopted approach in industry due to rare anomaly occurrences and data imbalance. A desirable characteristic of an UAD model is cont…
Edge Storage Management Recipe with Zero-Shot Data Compression for Road Anomaly Detection
YeongHyeon Park, Uju Gim, Myung Jin Kim
Recent studies show edge computing-based road anomaly detection systems which may also conduct data collection simultaneously. However, the edge computers will have small data stor…
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…