Enhancing Disaster Preparedness through Synthetic Data Generation in AI and Machine Learning
Data is often considered the lifeblood of machine learning algorithms. The availability of vast amounts of data has played a vital role in the rapid development of AI applications across various domains. However, a significant challenge that researchers and practitioners face in the AI landscape is the issue of data scarcity. Data scarcity refers to the limited availability or inadequacy of high-quality data for training AI models.