Title: Visible property enhancement techniques of IoT cameras using machine learning techniques

Authors: S. Narayanan; G. Hanumat Sastry; Shobha Aswal; Venkatadri Marriboyina; R. Sankaranarayanan; Varsha

Addresses: Department of Information Technology, SRM Valliammai Engineering College, Kattankulathur, 603203, Tamil Nadu, India ' School of Computer Science, University of Petroleum and Energy Studies, Dehradun, 248007, India ' School of Computing, Graphic Era Hill University, Dehradun, 248002, India ' Department of Computer Science and Engineering, SVKM's NMIMS MPSTME Shirpur, Maharashtra, 425405, India ' Department of Information Technology, SRM Valliammai Engineering College, Kattankulathur, 603203, Tamil Nadu, India ' CT Group of Engineering, Management and Technology, Lambri, Punjab, 144623, India

Abstract: Perceiving a sight in low light is challenging due to low SNR and photon counts. Deeper learning is a kind of machine learning that is revolutionising picture identification and computer perception. In this study, deeper learning will be used to enhance low-light picture filtering. To do this, a literature review will be performed to gather inspiration for methods and features that may be applied to the final networks. A fully functioning deeper learning picture filtering system will then be created, allowing networks to be trained using guided learning and the filtered resulting images to be recorded to files. With its output pictures plainly showing it was filtering low-light shots, the network functioned effectively. To maximise the network's potential, it must be run for a longer length of time.

Keywords: IoT cameras; visual improvement; SNR; signal to noise ratio; machine learning; ML.

DOI: 10.1504/IJNT.2023.134015

International Journal of Nanotechnology, 2023 Vol.20 No.5/6/7/8/9/10, pp.569 - 585

Received: 25 Aug 2021
Accepted: 14 Dec 2021
Published online: 10 Oct 2023 *

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