Mrinalini Singh

Work place: SCOPE, Vellore Institute Technology, Vellore, TN, India



Research Interests: Image Processing, Network Security, Computer Vision, Computational Learning Theory


Ms. Mrinalini Singh is Graduate of Bachelor’s of Technology in Computer Science and Engineering at Vellore Institute of Technology, India. She is an aspiring programmer, and event manager. She has developed interests in latest technologies like Block Chain technologies, Speech Recongnization, App desinging, Google Cloud technologies. Her major fields of interest include Network security, Block chain and Crypto currecy, Machine Learning, Computer Vision, Image Processing, Data Visualization and has worked on several research projects and papers for the same.

Author Articles
A Reinforcement Learning-based Offload Decision Model (RL-OLD) for Vehicle Number Plate Detection

By Yadavendra Atul Sakharkar Mrinalini Singh Kakelli Anil Kumar Aju D

DOI:, Pub. Date: 8 Dec. 2021

Vehicle license number plate detection is essential for road safety and traffic management. Many existing systems have been proposed to achieve high detection precision without optimization of computer resources. Existing models have not preferred to use devices like smartphones or surveillance cameras because of high latency, data loss, bandwidth costs, and privacy. In this article, we propose a model of unloading decisions based on reinforcement learning (RL-OLD) for recognition and detection of vehicle license plates for high precision with optimization of computer resources. The proposed model detected different categories of vehicle registration plates by effectively utilizing edge computing. Our model can choose either the compute-intensive model of the cloud or the lightweight model of the local system based on the properties of the number plate. This approach has achieved high accuracy, limited data loss, and limited latency.

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