Here are the top CNN interview questions to prepare for your next role.
1️⃣ What is the role of the activation function in CNNs?
- A) To introduce non-linearity into the model
- B) To normalize the input data
- C) To reduce the dimensionality of the input data
- D) To increase the computational complexity
2️⃣ What are some common CNN architectures?
- A) LeNet
- B) Inception
- C) ResNet
- D) Decision Trees
3️⃣ What is a feature map?
- A) A matrix storing the weights used in a convolutional neural network (CNN)
- B) A graph depicting the loss function of a neural network during training
- C) A representation of the input image after applying a convolution operation that highlights specific features
- D) An array containing the pixel values of the input image before any processing
4️⃣ What is a receptive field in the context of CNNs?
- A) The area of the input image that is discarded during processing
- B) The area of the output image that a particular neuron can see
- C) The memory allocated for processing a particular portion of the input image
- D) The area of the input image that a particular neuron can see
5️⃣ What is padding in a convolutional layer?
- A) Padding refers to adding extra spaces around the input data before applying convolution.
- B) Padding increases the size of the kernel used in convolution.
- C) Padding helps prevent overfitting during model training.
- D) Padding reduces the dimensionality of the input data.