“Parameter sharing" - A benefit of using convolutional networks. Which of the following statements about parameter sharing in CNN are true?Question 1Answera. It reduces the total number of parameters, thus reducing overfitting.b. More than one option is correctc. It allows parameters learned for one task to be shared even for a different task (transfer learning).d. It allows a feature detector to be used in multiple locations throughout the whole input image/input volume.
Question
“Parameter sharing" - A benefit of using convolutional networks. Which of the following statements about parameter sharing in CNN are true?Question 1Answera. It reduces the total number of parameters, thus reducing overfitting.b. More than one option is correctc. It allows parameters learned for one task to be shared even for a different task (transfer learning).d. It allows a feature detector to be used in multiple locations throughout the whole input image/input volume.
Solution
The correct answer is b. More than one option is correct.
This is because both statements a, c, and d are true about parameter sharing in Convolutional Neural Networks (CNNs).
a. Parameter sharing significantly reduces the total number of parameters in the model, which helps to reduce overfitting.
c. Parameter sharing allows for transfer learning, where parameters (or learned knowledge) of one model can be used in another task. This is particularly useful when the amount of data for the new task is limited.
d. Parameter sharing allows a feature detector to be used across the entire input image/volume. This means that the feature detector can recognize patterns regardless of their location in the input, providing the CNN with a form of translation invariance.
Similar Questions
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