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AuthenTech employs cutting-edge technology to verify online purchases' authenticity. It's a vital tool in combating counterfeit items, leveraging advanced algorithms and image recognition. Tailored for both consumers and retailers.

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AuthenTech: Counterfeit Detection using TensorFlow

Overview AuthenTech is a project designed to distinguish between counterfeit and original items using convolutional neural networks (CNNs) and TensorFlow.

Tech Stack TensorFlow: For building and training the CNN model.

Python: Main programming language.

JSON: For loading label data.

OpenCV (cv2): For image processing.

Keras: High-level neural networks API integrated with TensorFlow.

Objectives

Accuracy: High accuracy in distinguishing counterfeit items.

Robustness: Generalize well to unseen data.

Efficiency: Quick image processing for real-time applications.

Impact: Provide a reliable tool against counterfeiting.

Prerequisites

Install TensorFlow: pip install tensorflow

Install OpenCV: pip install opencv-python

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AuthenTech employs cutting-edge technology to verify online purchases' authenticity. It's a vital tool in combating counterfeit items, leveraging advanced algorithms and image recognition. Tailored for both consumers and retailers.

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