4 papers
Statistical Non-linear Reconstruction Loss for Image Anomaly Detection
Nguyen Minh Tri, Hoang Khuong Duy, Huynh Cong Viet Ngu
Reconstruction-based methods are a cornerstone of unsupervised image anomaly detection, but they remain vulnerable to \emph{outlier leakage}, where standard mean squared error (MSE…
BoRAD: Bootstrap your Own Representations for Multi-class Anomaly Detection
Duy Hoang Khuong, Tri Nguyen Minh, Ngu Huynh Cong Viet
Reconstruction-based anomaly detection is attractive for industrial inspection, but scaling it from category-specific training to a one-for-all setting is challenging. A single mod…
Improving Imbalanced Multi-Label Chest X-Ray Diagnosis via CBAM-Enhanced CNN Backbones
Duy Nguyen Huu, Duy Hoang Khuong, Ngu Huynh Cong Viet
Chest radiography is a widely used imaging modality for thoracic disease diagnosis, yet its conventional interpretation remains time-consuming and heavily dependent on expert knowl…
Momentum-Anchored Multi-Scale Fusion Model for Long-Tailed Chest X-Ray Classification
Duy Hoang Khuong, Duy Nguyen Huu, Ngu Huynh Cong Viet
Chest X-ray classification suffers from severe class imbalance where gradient updates bias toward majority classes, causing feature drift and poor performance on rare but critical…