Model1 1. Model Model 1 : 3 Layers with 1 Convolution layer 2. Training with Training loss 3. Test Accuracy 4. Images and corresponding probability that predicted Right 5. Images and corresponding probability that predicted Wrong Model2 1. Model Model 2 : 5 Layers with 2 Convolution layer 2. Training with Training loss 3. Test Accuracy 4. Images and corresponding probability that predicted Right 5. Images and corresponding probability that predicted Wrong Model3 1. Model Model 3 : 7 Layers with 4 Convolution layer 2. Training with Training loss 3. Test Accuracy 4. Images and corresponding probability that predicted Right 5. Images and corresponding probability that predicted Wrong
