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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
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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 : 19451
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
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| Paper Title: | Quantization of Convolutional Neural Networks: A Practical Approach |
| Authors Name: | Dwith Chenna |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_188603
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| Published Paper Id: | IJRTI2312025 |
| Published In: | Volume 8 Issue 12, December-2023 |
| DOI: | https://doi.org/10.5281/zenodo.10341014 |
| Abstract: | Deep neural networks play a critical role in the remarkable developments in the field of computer vision. Convolutional Neural Networks (CNN), widely used in computer vision tasks, require substantial computation and memory resources, making it challenging for these models to run on resource-constrained devices. Quantization is an efficient way to reduce the compute and memory footprint of these models, making it possible to run them on edge devices. Many techniques have been studied to allow practical applications of quantization CNN models on mobile or edge devices. The practical implementation and adoption of these quantization techniques is heavily limited by approaches available in tools i.e. TFlite/Pytorch and underlying hardware. However, possible degradation in performance makes it challenging to achieve comparable performance to the original float-point model. In this paper, we will review different aspects of quantization, including assumptions, best practices, tools, and recipes to get the best results from quantization. |
| Keywords: | Quantization, Convolutional Neural Networks |
| Cite Article: | "Quantization of Convolutional Neural Networks: A Practical Approach", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 12, page no.181 - 192, December-2023, Available :http://www.ijrti.org/papers/IJRTI2312025.pdf |
| Downloads: | 000205181 |
| 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: IJRTI2312025
Registration ID:188603
Published In: Volume 8 Issue 12, December-2023
DOI (Digital Object Identifier): https://doi.org/10.5281/zenodo.10341014
Page No: 181 - 192 Country: San Jose, California, United States Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2312025 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2312025 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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