/Auto-tag_Images_of_the_Gala

Deep Learning - Image Detection

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Deep Learning—Auto-tag Images of the Gala

Categorical Image recognition using deep learning models:

CNN Model with Regularization CNN Model with Image Augmentation Leveraging Transfer Learning with Pre-trained CNN Models VGG-16 model Pre-trained CNN model as a Feature Extractor with Image Augmentation

The 'Auto-tag Images of the Gala' data consists of 11000 32x32 color images in 4 classes. There are 6000 training images and 5000 test images in the data.

The label classes in the dataset are:

  1. Food
  2. misc
  3. Attire
  4. Decorationandsignage

Deep Learning Problem:

  1. Detect and recognise the objects/images from the data set with optimum accuracy.
  2. Accuracy should be considerably higher.
  3. There is no time constraint.

Steps followed to solve the problem:

  1. Load and pre-process the data
  2. Define the model’s architecture
  3. Train the model
  4. Make predictions