TFIGF: Fire data augmentation model based on text-to-image synthesis

Key Points

• Text-to-image synthesis improves the generation of synthetic fire data images, enhancing model performance.
• The proposed generative model demonstrates a 30% increase in accuracy during fire detection tasks.
• Data augmentation techniques focus on enlarging training datasets, which is crucial for effective machine learning applications.
• Highlights the potential of synthetic data in machine learning, suggesting further application in real-world scenarios.