Browsing by Author "HAMZA IQBAL, ZAEEM UL ISLAM, MOBEEN KHALID and MUHAMMAD MEHMOOD"

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    AI Based Self-Checkout System
    (UMT, Lahore, 2024) HAMZA IQBAL, ZAEEM UL ISLAM, MOBEEN KHALID and MUHAMMAD MEHMOOD
    This paper proposes to design and implement a system that automates the checkout process in retail stores using AI and computer vision. The system would be implemented in a modular attachable box the size of a standard checkout counter. This system will be implemented using the concepts of computer vision and convolutional neural networks on a dataset of ten Swiss retail products of various categories. Moreover, this project also implements a self-checkout system using the concept of computer-vision and deep learning. It will use the lengths and widths of object detected and also apply a text recognition algorithm to extract text from it that will help the system identify the exact product. This will also lead to less wait time for the customer, thus improving their satisfaction and preventing outbursts or complaints by the customer. The primary focus of this system is not eliminating the need of cashiers but to reduce the wait time at checkout lanes.