Traffic Sign Classification Quiz

Which Python library is most commonly used to implement Convolutional Neural Networks (CNNs) for image classification tasks?

• Pandas

• Keras

• NumPy

• Matplotlib

In a CNN implementation, what does the Conv2D function in Keras do?

• Adds a dense (fully connected) layer

• Adds a convolutional layer that applies filters to the input image

• Reduces the image dimensions by pooling

• Compiles the model

Which of the following code snippets is used to add a max pooling layer in a Keras-based CNN?

• MaxPooling2D(pool_size=(2, 2))

• Dropout(0.5)

• Dense(128)

• Conv2D(32, (3, 3))

Which function is used to compile a CNN model in Keras?

• model.add()

• model.compile()

• model.fit()

• model.evaluate()

What argument is typically passed to the activation parameter in a Conv2D layer for traffic sign classification?

• "relu"

• "sigmoid"

• "tanh"

• "softmax"

Which of the following functions is used to train a CNN model in Keras?

• model.compile()

• model.summary()

• model.fit()

• model.predict()

When working with traffic signimages, which function is used to preprocess the image data for input into a CNN?

• train_test_split()

• ImageDataGenerator()

• to_categorical()

• fit_transform()

In the context of CNNs, what is the purpose of the Flatten() function in Keras?

• To add a convolutional layer

• To transform the input data into a 1D vector

• To add a pooling layer

• To normalize the input data

Which of the following loss functions is most commonly used in a CNN for multi-class traffic sign classification?

• binary_crossentropy

• mean_squared_error

• categorical_crossentropy

• hinge

After training a CNN, which function is used to evaluate its performance on the test data?

• model.fit()

• model.summary()

• model.evaluate()

• model.compile()