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Scenic

Scenic is a project that utilizes transfer learning with a pretrained ResNet model using TensorFlow/Keras for classifying natural scene images. The project leverages the Intel Image Classification Dataset for training and evaluation.

Features

  • Built using TensorFlow/Keras.
  • Employs transfer learning with pretrained ResNet weights for efficient feature extraction.
  • Classifies natural scenes into six categories: buildings, forest, glacier, mountain, sea, and street.

Dataset

Results

  • ResNet50 with transfer learning achieved 92% accuracy on the test dataset.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Acknowledgments

  • Dataset by Intel.
  • Pretrained ResNet weights from Keras Applications.
  • ResNet architecture: "Deep Residual Learning for Image Recognition".