EXPLORING SIMILAR IMAGE RETRIEVAL THROUGH RESNET-50 AND NEAREST NEIGHBOR TECHNIQUES

Registration ID: IJNRD_224937

Published ID: IJNRD2407178

: Click Here to Get

K.s. Bhavitha, Dr.N.Sudhakar Reddy

Image retrieval, Deep learning, ResNet-50, Nearest neighbors, Dimensionality reduction, Visualization, Computer vision.

Image retrieval, the task of finding similar images within a dataset, is a fundamental challenge in computer vision with numerous real-world applications. In this study, we explore the domain of image retrieval, aiming to develop an effective methodology for identifying visually similar images. Leveraging advanced deep learning techniques, particularly the ResNet-50 model, we extract high-dimensional feature representations from images, capturing their intrinsic visual characteristics. These features serve as the basis for training a nearest neighbor model, facilitating efficient similarity search based on Euclidean distance metrics. Furthermore, we employ dimensionality reduction techniques, including Principal Component Analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE), to visualize the underlying structure of the dataset. Through this visualization, we gain valuable insights into the distribution and clustering of images, aiding in the interpretation of retrieval results. Our work presents a comprehensive approach to image retrieval, integrating cutting-edge deep learning algorithms with classical machine learning techniques and visualization methods. By harnessing the power of artificial intelligence, we strive to advance the field of image analysis and enable more efficient and intuitive image retrieval systems for various applications.

Published Paper   E-Certificate

K.s. Bhavitha & Dr.N.Sudhakar Reddy (July-2024). EXPLORING SIMILAR IMAGE RETRIEVAL THROUGH RESNET-50 AND NEAREST NEIGHBOR TECHNIQUES. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(7), b753-b760. https://ijnrd.org/papers/IJNRD2407178.pdf

Volume 9 Issue 7, July-2024

Pages : b753-b760

Paper Reg. ID: IJNRD_224937

Published Paper Id: IJNRD2407178

Downloads: 000122257

Research Area: Computer Engineering 

Author Type: Indian Author

Country: CHITTOR, AP, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2407178.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2407178

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

UGC CARE JOURNAL PUBLICATION | 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

© 2025 — Authors hold the copyright of this article. This work is licensed under a Creative Commons Attribution 4.0 International License. and The Open Definition.

You are free to share, adapt, and redistribute the material, provided proper credit is given to the original author. 🛡️ Disclaimer: The content, data, and findings in this article are based on the authors’ research and have been peer-reviewed for academic purposes only. Readers are advised to verify all information before practical or commercial use. The journal and its editorial board are not liable for any errors, losses, or consequences arising from its use.

Call For Paper - Volume 10 | Issue 12 | December 2025

IJNRD is a Scholarly Open Access, Peer-Reviewed, Refereed, and UGC CARE Journal Publication 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, and Transparent Peer Review Journal Publication that adheres to the UGC CARE 2025 Peer-Reviewed Journal Policy and aligns with Scopus Journal Publication standards to ensure the highest level of research quality and credibility.

IJNRD offers comprehensive Journal Publication Services including indexing in all major databases and metadata repositories, Digital Object Identifier (Crossref DOI) assignment for each published article with additional fees, citation generation tools, and full Open Access visibility to enhance global research reach and citation impact.

The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse academic and professional fields. The journal promotes global knowledge exchange among researchers, developers, academicians, engineers, and practitioners, serving as a trusted platform for innovative, peer-reviewed journal publication and scientific collaboration.

Indexing Coverage: 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 other 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

You can now publish your research in IJNRD. IJNRD is a Transparent Peer-Reviewed Open Access Journal Publication (Refereed Journal), aligning with New UGC and UGC CARE recommendations.

For more details, refer to the official notice: UGC Public Notice

Submit Paper Online

Important Dates for Current issue

Paper Submission Open For: December 2025

Current Issue: Volume 10 | Issue 12 | December 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Dec-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

Approval, Licenses and Indexing: More Details