M
Manoj Sharma
Researcher at Council of Scientific and Industrial Research
Publications - 20
Citations - 159
Manoj Sharma is an academic researcher from Council of Scientific and Industrial Research. The author has contributed to research in topics: Image resolution & Deep learning. The author has an hindex of 6, co-authored 16 publications receiving 112 citations. Previous affiliations of Manoj Sharma include Central Electronics Engineering Research Institute & Indian Institute of Technology Delhi.
Papers
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Proceedings ArticleDOI
2D-3D CNN Based Architectures for Spectral Reconstruction from RGB Images
Sriharsha Koundinya,Himanshu Sharma,Manoj Sharma,Avinash Upadhyay,Raunak Manekar,Rudrabha Mukhopadhyay,Abhijit Karmakar,Santanu Chaudhury +7 more
TL;DR: This work proposes a 2D convolution neural network and a 3D convolved neural network based approaches for hyperspectral image reconstruction from RGB images that achieves very good performance in terms of MRAE and RMSE.
Journal ArticleDOI
Development and sliding wear behaviour of milled carbon fibre reinforced epoxy gradient composites
Navin Chand,Manoj Sharma +1 more
TL;DR: Milled carbon fibre reinforced epoxy gradient composites were developed at different centrifugation speeds having 3 wt% of milled carbon fiber Composites were also prepared at different RPMs There is a gradient formation at all the speeds, which has been confirmed by variation in density of different zones.
Journal ArticleDOI
Design of 42 GHz gyrotron for Indian fusion tokamak system
Udaybir Singh,Nitin Kumar,Hasina Khatun,Narendra Kumar,Vivek Yadav,Anil Kumar,Manoj Sharma,Mukesh Kumar Alaria,Anirban Bera,Pradip Kumar Jain,Ashok K. Sinha +10 more
TL;DR: The rigorous design simulations confirm more than 200 kW RF power generation in TE0,3 mode at 42 GHz frequency and experimental results of cold cavity analysis are presented.
Proceedings ArticleDOI
An End-to-End Trainable Framework for Joint Optimization of Document Enhancement and Recognition
Anupama Ray,Manoj Sharma,Avinash Upadhyay,Megh Makwana,Santanu Chaudhury,Akkshita Trivedi,Ajay Kumar Singh,Anil Kumar Saini +7 more
TL;DR: An end-to-end trainable deep-learning based framework for joint optimization of document enhancement and recognition, using a generative adversarial network (GAN) based framework to perform image denoising followed by deep back projection network (DBPN) for super-resolution.
A Study on Factor Influencing Satisfaction of Investors Towards Mutual Funds Industry Using Servqual Model: An Empirical Study
TL;DR: In this paper, the authors used SERVQUAL Model to identify the gaps between the expectation and satisfaction level of the customers and identified the factors which influence the satisfaction level with respect to mutual fund companies.