STD-net: saree texture detection via deep learning framework for E-commerce applications-Reference-Cited by-同舟云学术

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STD-net: saree texture detection via deep learning framework for E-commerce applications

Published:2023-09-27 Issue:1 Volume:18 Page:495-503
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Priya D. Karthika^ORCID,Bama B. Sathya,Ramkumar M. P.,Roomi S. Mohamed Mansoor

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s11760-023-02757-y.pdf

Reference33 articles.

1. https://www.livafluidfashion.com/pdf/India_Saree_Trends.pdf.

2. https://www.dollsofindia.com/library/saree/.

3. Stout, E.E.: Introduction to textiles. 3rd ed. New York, John Wiley and Sons, Inc. 363(1970).

4. Potter, M.D., Corbman. B.P.: Textiles: Fibre to fabric. New York, Macmillan Hill Co. 342 (1967).

5. Hollen, N., Saddler, J.: Textiles. 4th edition. New York, Macmillan Company. 219 (1973).

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Incremental-based YoloV3 model with hyper-parameter optimization for product image classification in E-commerce sector;Applied Soft Computing;2024-11

2. Sareenet: saree texture classification via region-based patch generation with an optimized efficient Aquila network;Opto-Electronics Review;2024-02-11

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