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Questions and Answers
What is the backbone of convolutional neural networks?
What is the backbone of convolutional neural networks?
- Feature extraction
- Classification task
- Convolution operation (correct)
- Pooling operation
Which step in a CNN involves dealing with non-linear data?
Which step in a CNN involves dealing with non-linear data?
- Classification
- Convolution
- Feature extraction
- Applying non-linearity (correct)
What is the goal of image classification using CNNs?
What is the goal of image classification using CNNs?
- Extracting images from features
- Applying non-linearity to features
- Applying pooling operations
- Learning features directly from data (correct)
In a CNN, what does the application of non-linearity help with?
In a CNN, what does the application of non-linearity help with?
Which operation is responsible for extracting features in a CNN?
Which operation is responsible for extracting features in a CNN?
How do CNNs utilize convolutions for solving computer vision tasks?
How do CNNs utilize convolutions for solving computer vision tasks?
What is the purpose of the pooling operation in a CNN?
What is the purpose of the pooling operation in a CNN?
How are classical scores computed in image classification using CNNs?
How are classical scores computed in image classification using CNNs?
What does each neuron in the hidden layer compute in a CNN during the convolution operation?
What does each neuron in the hidden layer compute in a CNN during the convolution operation?
Which layer in a CNN is responsible for detecting specific features in localized areas of the input image?
Which layer in a CNN is responsible for detecting specific features in localized areas of the input image?
What is a key characteristic of local connectivity in CNNs?
What is a key characteristic of local connectivity in CNNs?
What is the purpose of applying a bias in a neuron during a convolution operation in a CNN?
What is the purpose of applying a bias in a neuron during a convolution operation in a CNN?
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