Super Image Resolution

Registration ID: IJNRD_197137

Published ID: IJNRD2305765

DOI: Click Here to Get

Rituraj Mishra , Neha Chauhan , Preeti Dwivedi

CNN, SSIM, PSNR, RFDN, Autoencoders, Image Resolution

Deep Literacy necessitates a significant amount of info. This phrase has gained popularity among those who are considering applying deep literacy methods to their data. Enterprises regularly make significant decisions based on the prevalent idea that deep literacy only works with vast amounts of data when they do not have "big" enough data. This is not correct. Although huge amounts of data are required in some circumstances, some networks may be trained on a single image. Furthermore, without big datasets, the topology of the network itself may prevent deep networks from over-fitting in practise. We propose a deep literacy system for single-image super-resolution (SR) in this design. Our algorithm learns an end-to-end mapping between low/high quality pictures immediately. The mapping is represented by a deep convolutional neural network (CNN) that accepts the low-resolution picture as input and labours to produce the high-resolution image. We also demonstrate that classic meager-coding-based SR methods may be termed deep convolutional networks. However, unlike standard styles that manage each element individually, our method optimises all levels together. Our deep CNN has a featherlight construction yet achieves state-of-the-art restoration quality and quick speed for practical online operation. We experiment with various network architectures and parameter settings to find the best balance of performance and speed. In addition, we expand our network to handle three colour channels concurrently and demonstrate improved overall reconstruction quality.

Published Paper   E-Certificate

Rituraj Mishra, Neha Chauhan, & Preeti Dwivedi (May-2023). Super Image Resolution. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), h479-h483. https://ijnrd.org/papers/IJNRD2305765.pdf

Volume 8 Issue 5, May-2023

Pages : h479-h483

Paper Reg. ID: IJNRD_197137

Published Paper Id: IJNRD2305765

Downloads: 000121976

Research Area: Health Science 

Country: Lucknow, UTTAR PRADESH, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305765.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305765

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave | IJNRD.ORG | IJNRD.COM | IJPUB.ORG

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.

Indexing Coverage includes Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar (AI-Powered Research Tool), Microsoft Academic, Academia.edu, arXiv.org, ResearchGate, CiteSeerX, ResearcherID (Thomson Reuters), Mendeley, DocStoc, ISSUU, Scribd, and many more recognized academic repositories.

How to submit the paper?

By Our website

Click Here to Submit Paper Online

By Mail

Send your paper to editor@ijnrd.org

Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.

Subject Category: Research Area

Call for Paper: More Details