Detect Genuine And Counterfeit Logos Using A Cnn With The Inception V3 Pre Trained Model To Achieve High accuracy

• Author(s):

  Mrs. J.Jenila, Ap/CSE | Dharni Ritika KG | Gayathri B | Keerthana S

• Keywords:

  Counterfeit Detection, Logo Recognition, Inception-V3, Deep Learning, Convolutional Neural Networks.

• Abstract:

  The Proliferation Of Counterfeit Products Poses Significant Challenges To Brand Integrity And Consumer Trust. This Paper Presents A Comprehensive Survey On Detecting Genuine And Counterfeit Logos Using Convolutional Neural Networks (CNNs) With The Inception-V3 Pre-trained Model. We Review Recent Advancements In Deep Learning-based Logo Detection, Focusing On Accuracy, Robustness, And Computational Efficiency. The Survey Highlights Key Methodologies, Datasets, Performance Metrics, And Challenges In This Domain. Our Analysis Demonstrates That Inception-V3, Combined With Fine-tuning And Data Augmentation, Achieves State-of-the-art Performance In Distinguishing Authentic And Counterfeit Logos. Future Research Directions Include Improving Generalization Across Diverse Logo Designs And Integrating Explainable AI Techniques For Enhanced Interpretability.

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Other Details

• Paper id:

  IJSARTV11I3102953

• Published in:

  Volume: 11 Issue: 3 March 2025

• Publication Date:

  2025-03-31

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