QUESTION 11 Which of the following is/are true about fine tuning? Hint: See section 5.3.2 All layers of the frozen model base used for feature extraction are trained on new data Fully connected layers are jointly trained with top convolution layers. Top layers of the frozen model base used for feature extraction can be trained on new data Only Fully connected layers are trained QUESTION 12 Which of the following is/are true about visualization the various layers in convnets? The first layer acts as a collection of various edge detectors. As you go higher i.e. more deeper layers, the activations encode higher level concepts. As you go higher i.e. more deeper layers, the activations become increasingly abstract and less visually interpretable. The probability of finding blank outputs gets higher as some filters have no matching pattern in the image

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
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QUESTION 11
Which of the following is/are true about fine tuning?
Hint: See section 5.3.2
All layers of the frozen model base used for feature extraction are trained on new data
Fully connected layers are jointly trained with top convolution layers.
Top layers of the frozen model base used for feature extraction can be trained on new data
Only Fully connected layers are trained
QUESTION 12
Which of the following is/are true about visualization the various layers in convnets?
The first layer acts as a collection of various edge detectors.
As you go higher i.e. more deeper layers, the activations encode higher level concepts.
As you go higher i.e. more deeper layers, the activations become increasingly abstract and less visually interpretable.
The probability of finding blank outputs gets higher as some filters have no matching pattern in the image
Transcribed Image Text:QUESTION 11 Which of the following is/are true about fine tuning? Hint: See section 5.3.2 All layers of the frozen model base used for feature extraction are trained on new data Fully connected layers are jointly trained with top convolution layers. Top layers of the frozen model base used for feature extraction can be trained on new data Only Fully connected layers are trained QUESTION 12 Which of the following is/are true about visualization the various layers in convnets? The first layer acts as a collection of various edge detectors. As you go higher i.e. more deeper layers, the activations encode higher level concepts. As you go higher i.e. more deeper layers, the activations become increasingly abstract and less visually interpretable. The probability of finding blank outputs gets higher as some filters have no matching pattern in the image
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