Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM32018
Volume:
8 |
4 |
Apr 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Identifying authenticated sarees through human vision and feel is a challenging aspect. Secondly Saree industry is multibillion businesses in Indian Industry. Each silk saree cost range from Rs 10000 to Rs 500000. Every consumer tries to identify authenticated saree before purchasing. With today’s technology changes we have prepared novel approach to detect the authentication of the saree. This work offers a method for classifying and detecting saree types using computer vision techniques. The visual features of sarees are classified by machine learning and image processing; preprocessing improves the classification model. With the use of region based CNNs (RCNN) extract texture features that are essential for differentiating Kanchivaram Silk Sarees. The model ensures stability across datasets and training conditions, as demonstrated by experimental findings that show its improved accuracy and speed over traditional deep learning techniques. This research increases computer vision in apparel recognition and categorization with applications in e-commerce and fashion recommendation.
KEYWORDS
Publication Date
12/31/45409
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
1
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...