/FruitFinder

An exploration of various Convolutional Neural Network architectures and techniques on the Fruits-360 Dataset. This serves as the source code for the Google Colab Notebook which handles this content

Primary LanguagePython

FruitFinder

An exploration of various Convolutional Neural Network architectures and techniques on the Fruits-360 Dataset. This serves as the source code for the Google Colab Notebook which handles this content

Techniques Used

  • Convolutional Neural Networks with TensorFlow and Keras
  • Skip Connections
  • Inception Modules
  • Dropout and Batch Normalization
  • Activation Analysis

Please see the notebook for the implementation of these techniques.