AI-Powered Lost and Found: Bridging Subjective Descriptions with Image Analysis

This research explores using generative AI to bridge the gap between subjective descriptions and actual item characteristics in lost and found systems. The approach leverages image analysis to extract features, aiming to refine user queries effectively. The key lies in the AI's ability to translate vague descriptions into concrete visual attributes.

• •The research aims to improve lost item retrieval by leveraging AI.
• •It addresses the issue of subjective and vague descriptions of lost items.
• •Generative AI is used to extract features like color, shape, and pattern from images.