Deep learning applications in brand identity protection: A technical analysis

Pelluru, Prem Sai (2025) Deep learning applications in brand identity protection: A technical analysis. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 1194-1205. ISSN 2582-8266

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Abstract

This technical article explores deep learning applications for brand identity protection through visual content analysis, focusing specifically on convolutional neural networks in e-commerce environments. We present an empirically validated framework that integrates optimized CNN architectures, multi-modal feature engineering, and scalable system design to address counterfeit detection challenges in digital marketplaces. The framework achieves over 95% detection accuracy while maintaining sub-100ms latency in production environments. We address key technical challenges including visual variations handling and false positive mitigation, provide detailed performance metrics, and explore emerging approaches in self-supervised learning, few-shot learning, and federated systems that promise to further advance brand protection capabilities.

Item Type: Article
Official URL: https://doi.org/10.30574/wjaets.2025.15.1.0356
Uncontrolled Keywords: Brand Protection; CNN Architecture; Deep Learning; E-Commerce Security; Visual Analysis
Depositing User: Editor Engineering Section
Date Deposited: 04 Aug 2025 16:09
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/2896