Self-Supervised Depression Detection with Time-Frequency Fusion
Published:Dec 14, 2025 07:53
•1 min read
•ArXiv
Analysis
This research explores a self-supervised approach to depression detection, utilizing time-frequency fusion and multi-domain cross-loss. The ArXiv publication suggests a novel methodology in a significant area of mental health, paving the way for potential advancements in diagnostic tools.
Key Takeaways
Reference
“The research focuses on self-supervised depression detection.”