Efficient Multimodal Similarity Search using Vector Database and Deep Embedding Model

Author(s)	Ms. Sara Tabassum, Dr. Rashmi CR, Prof. Dr. Shantala CP
Country	India
Abstract	This paper is about a system that helps with finding information in a better way. It uses a model called CLIP that takes words and pictures and turns them into something that a computer can understand. This system can also make pictures, videos and sounds from words. All the new things it makes and the understanding of the words and pictures are stored in a database called LanceDB. This makes it easy to find things that're similar to what you are looking for. The system also has a web interface that people can use to make new things and look for things in real time. The people who made this system tested it. Found out that it works well and can find things quickly. The system is good at understanding what people mean when they use words to search for things. It can do this across different types of media, like pictures, videos and sounds.
Keywords	Multimodal retrieval, Cross-modal search, Vector database, LanceDB, CLIP, Diffusion models, Gradio web interface.
Field	Engineering
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-23

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International Journal For Multidisciplinary Research