Convolution Neural Network Quiz

1. ____________ in which we give input to our model.

• A. Input layer

• B. Output layer

• C. Hidden layer

• D. None of these

2. The input from Input layer is then feed into the______.

• A. Input layer

• B. Output layer

• C. Hidden layer

• D. None of these

3. The data is then fed into the model and output from each layer is obtained this step is called _______.

• A. Feedforward

• B. Feed backward

• C. input layer

• D. Output layer

4. In ____________ holds the raw input of image used to build ConvNets.

• A. Input Layer

• B. Convolution Layer

• C. Activation Function Layer

• D. Pool Layer

5. ____________ computes the output volume by computing dot product between all filters and image patch.

• A. Input Layer

• B. Convolution Layer

• C. Activation Function Layer

• D. Pool Layer

6. __________ will apply element wise activation function to the output of convolution layer.

• A. Input Layer

• B. Convolution Layer

• C. Activation Function Layer

• D. Pool Layer

7. _________ common types of pooling layers.

• A. 2

• B. 3

• C. 4

• D. 5

8. _________ is a pooling operation that selects the maximum element from the region of the feature map covered by the filter.

• A. Max Pooling

• B. Average Pooling

• C. Global pooling

• D. None of these

9. ________ computes the average of the elements present in the region of feature map covered by the filter.

• A. Max Pooling

• B. Average Pooling

• C. Global pooling

• D. None of these

10. ___________ reduces each channel in the feature map to a single value.

• A. Max Pooling

• B. Average Pooling

• C. Global pooling

• D. None of these