DeepCQ: Predicting Quality in Lossy Compression with Deep Learning
Research#Compression🔬 Research|Analyzed: Jan 10, 2026 07:30•
Published: Dec 24, 2025 21:46
•1 min read
•ArXivAnalysis
This ArXiv paper introduces DeepCQ, a general-purpose framework that leverages deep learning to predict the quality of lossy compression. The research has potential implications for improving compression efficiency and user experience across various applications.
Key Takeaways
- •DeepCQ is a deep-surrogate framework for predicting the quality of lossy compression.
- •The framework is designed to be general-purpose, suggesting broad applicability.
- •The research originates from the ArXiv pre-print server, indicating preliminary findings.
Reference / Citation
View Original"The paper focuses on lossy compression quality prediction."