Pattern Recognition Using Artificial Neural Networks

1. Pattern Recognition Using Artificial Neural Networks Ace of Hearts Eyal Ittah (60407301) Ittai Doron (53084489)

2. Introduction • Classify images of playing cards by their suit and value

3. Pattern Recognition • Sensor – existing images • Feature extraction mechanism – Relaxation Labeling on color images • Classification scheme –Artificial Neural Network used to classify suit and value

4. Relaxation Labeling • Objects – pixels • Labels – object, background • Initial confidence – degree of white

5. Artificial Neural Networks • Neurons as basic calculation units • Input layer - Each neuron a single input variable • Hidden layers • Output layer - Each neuron represents a single output variable.

6. Artificial Neural Networks • Training the network • Supervised learning • Back-propagation • Learning rate

7. Card classification

8. Card classification (noisy image)

9. Conclusions • Using two ANNs instead of one • Decreasing the learning rate of the ANN • Using an output neuron for each class