Sunil Maggu
@it.mait.ac.in
Assistant Professor in Information Technology Department
Maharaja Agrasen Institute of Technology, New Delhi
EDUCATION
Science), M.E(Computer Science), B.E.(Computer Science)
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Artificial Intelligence, Software
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
Kamaljot Singh, Md. Shadab Hussain, Seema Kalonia, Vandana Choudhary, Sunil Maggu, and Ajay Kumar Kaushik
IEEE
Image dehazing is a crucial low-level vision task that recovers clear images from hazy ones. In recent years, immense progress has been made in recovering the original image as accurately as possible, without any consideration for efficiency and performance on low-end hardware, making it a mere relic for image beautification. Image dehazing could be very critical for enhanced visibility during indoor emergencies like fire hazards, utilization in surveillance and security cameras and in autonomous vehicles, and hence should be quick and easy to compute in order to be accessible. Therefore, we propose LightClearNet, a lightweight yet just as effective model for single image dehazing based around batch normalization and skip connections. The model has been trained on RESIDE-6K dataset and our lightweight model delivers comparable results to DehazeFormer while being twice as performant as the lightest variant of DehazeFormer.
Hemant Kumar Upadhyay, Sapna Juneja, Sunil Maggu, Grima Dhingra, and Abhinav Juneja
Emerald
Purpose The purpose of current analytical work is to identify the critical barriers in social isolation in India amid Coronavirus infection disease (COVID) outbreak using the fuzzy-analytical hierarchical process (AHP) method. Design/methodology/approach The conventional AHP is insufficient for tackling the vague nature of linguistic assessment. Fuzzy AHP had been developed to resolve the hierarchical fuzzy problems, avoiding its risks on performance. In AHP, all comparisons are not included; thus, to find the priority of one decision variable over other, triangular fuzzy numbers are used. Findings A total of eight critical barriers in social distancing in India during COVID-19 have been compared and ranked. Dense population has emerged as the most culpable barrier in social isolation in India amid COVID outbreak followed by compulsion for pecuniary earning and general incautiousness. A total of eight critical barriers in social distancing in India during COVID-19 in four categories (societal barriers, insufficient facilitation barriers, growth-related barriers and population related barriers) have been compared and ranked. Originality/value On the basis of the numeral values, “growth-related barriers” attained top position followed by “population-related barriers” and “insufficient facilitation barriers.” The current work has explored the possible factors which can become key game changers to control the pace of spread of the pandemic.