4 papers
PC-MCL: Patient-Consistent Multi-Cycle Learning with multi-label bias correction for respiratory sound classification
Seung Gyu Jeong, Seong-Eun Kim
Automated respiratory sound classification supports the diagnosis of pulmonary diseases. However, many deep models still rely on cycle-level analysis and suffer from patient-specif…
Adaptive Knowledge Distillation using a Device-Aware Teacher for Low-Complexity Acoustic Scene Classification
Seung Gyu Jeong, Seong Eun Kim
In this technical report, we describe our submission for Task 1, Low-Complexity Device-Robust Acoustic Scene Classification, of the DCASE 2025 Challenge. Our work tackles the dual…
Patient Domain Supervised Contrastive Learning for Lung Sound Classification Using Mobile Phone
Seung Gyu Jeong, Seong Eun Kim
Auscultation is crucial for diagnosing lung diseases. The COVID-19 pandemic has revealed the limitations of traditional, in-person lung sound assessments. To overcome these issues,…
Patient-Aware Feature Alignment for Robust Lung Sound Classification:Cohesion-Separation and Global Alignment Losses
Seung Gyu Jeong, Seong Eun Kim
Lung sound classification is vital for early diagnosis of respiratory diseases. However, biomedical signals often exhibit inter-patient variability even among patients with the sam…