Implement a Convolution Neural Network IT Assignment Help
- Country :
India
Assignment Task
The Tasks
1. Separate out the card images from the train-XXX.jpg groups of images. Other than for those in train-001.jpg, in your code you will want to associate each card with its ID number.
2. Using image features, such as colour, histogram-of-gradients (e.g. SIFT/SURF), and/or texture or Gabor features, write a feature based matcher to compare pairs of card images and determine if they are similar. Using your image matcher, on all the 'unidentified' cards in train-001.jpg to find the closest M matches, e.g. M = 5, from all the other cards in the training images
3. Implement a convolutional neural network to predict the ID of any card using images from train-XXX and test-XXX. As there are not many examples, you will need to think about how to prevent overfitting. Test your solution on examples from both train-XXX and testXXX images. If you like, you may choose to use transfer-learning. Demonstrate the performance of your predictor using appropriate train-validate-test splits, and giving qualitative and quantitative results of your validation.
4. Devise a method to locate and identify cards in selected frames from video-001 and video-002. You may want to use one of the matchers you have developed in steps 2 or 3. Validate and demonstrate the performance of your method.
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