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Key Insights from the Analysis

Key Insights from the Analysis

The project reveals several important observations.

  • The CNN achieved higher classification accuracy than the ANN.
  • Normalizing pixel values improved the model's training performance.
  • Convolution layers automatically extracted useful image features.
  • Pooling layers reduced the size of feature maps while preserving important information.
  • The CNN classified unseen images more accurately than the ANN.
  • TensorFlow and Keras simplified the process of building and training deep learning models.

These insights demonstrate why CNNs are the preferred choice for image classification tasks.


Building an Image Classification System Using CNN

VA

Vishalini A





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