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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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Issue: December 2025
Volume 10 | Issue 12
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19455
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
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Published Paper Details
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| Paper Title: | Automated Image Colorization Using Deep Learning Techniques |
| Authors Name: | Kritarth Pandey , Renuka Lahare , Neha Gupta , Lavanya Ramteke , Swati Bhatt |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_201455
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| Published Paper Id: | IJRTI2503128 |
| Published In: | Volume 10 Issue 3, March-2025 |
| DOI: | http://doi.one/10.1729/Journal.44235 |
| Abstract: | This paper presents a CNN-driven approach for the automated colorization of grayscale images, eliminating the need for human intervention. Our method is built on the ECCV16 model, redefining the conventional regression problem as a classification task by quantizing the color space. We explore various network configurations, integrating batch normalization and dilated convolutions to improve model robustness and contextual perception. By leveraging this classification-based strategy, our model achieves more vibrant and natural colorizations than traditional regression techniques, affirming the effectiveness of our design choices. Additionally, a web-based interface showcases the practical usability of our system, while experimental findings highlight potential avenues for advancing automated image colorization. |
| Keywords: | CNN based approach, ECCV16 architecture, deep learning, image colorization, dilated convolution, encoder-decoder, flask, Responsive UI. |
| Cite Article: | "Automated Image Colorization Using Deep Learning Techniques", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 3, page no.b226-b231, March-2025, Available :http://www.ijrti.org/papers/IJRTI2503128.pdf |
| Downloads: | 000400 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2503128
Registration ID:201455
Published In: Volume 10 Issue 3, March-2025
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.44235
Page No: b226-b231 Country: Pune, Maharastra, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2503128 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2503128 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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