4 accepted papers
Tumor detection and classification in medical images are critical for guiding patient management and treatment decisions. However, accurate segmentation and classification of tumors remain challenging due to their small size relative to the overall image. Existing approaches often face difficulties…
Recent studies have demonstrated the effectiveness of fine-tuning self-supervised speech representation models for speech emotion recognition (SER). However, applying SER in real-world environments remains challenging due to pervasive noise. Relying on low-accuracy predictions due to noisy speech ca…
Automated auscultation and cardiovascular screening systems for cardiac abnormalities have received growing interest in clinical applications. Still, they face challenges due to missing or invalid recordings caused by technical issues. To address this, we introduce a novel framework leveraging the m…
Automated auscultation analysis using electronic stethoscope has received growing interest in clinical applications. Recently, researchers showed successes by using deep learning methods to distinguish between pathological respiratory sound classes. Nevertheless, the challenge persists due to the sc…