Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/175953
Title: Mobile-SAM in everyday object recognition application
Authors: Chen, Xiangyu
Keywords: Computer and Information Science
Issue Date: 2024
Publisher: Nanyang Technological University
Source: Chen, X. (2024). Mobile-SAM in everyday object recognition application. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175953
Project: SCSE23-0331 
Abstract: The digital transformation of educational tools has opened avenues to enhance cognitive development in children, particularly in recognizing and naming everyday objects. The development of the application aims to utilise the advancements of Computer Vision (CV) and Segment Anything Model (SAM) to create a more interactive and technologically enriching experience for children. This project will integrate SAM, specifically MobileSAM variant that is optimized for mobile platforms, and GroundingDino framework to deliver an engaging user interface. The project is also backed by extensive research and testing to select the most suitable CV model, ensuring a seamless interaction with real time image processing capabilities.
URI: https://hdl.handle.net/10356/175953
Schools: School of Computer Science and Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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