[10 points] VGG16 is a convolutional neural network model proposed by K. Simonya and A. Zisserman from the University of Oxford. The model achieves 92.7% top-5 test accuracy in ImageNet. VGG16 is shown in the figure below. Explain the model composition, how it works, and why in your opinion it is able to achieve such a high performance? 224 x 224 x 3 224 x 224 x 64 112 x 112 x 128 56 x 56 x 256 7 x 7 x 512 28 x 28 x 512 14 x 14 x 512 1 x 1 x 4096 1 x 1 x 1000 convolution+ReLU max pooling fully nected+ReLU softmax 0000
[10 points] VGG16 is a convolutional neural network model proposed by K. Simonya and A. Zisserman from the University of Oxford. The model achieves 92.7% top-5 test accuracy in ImageNet. VGG16 is shown in the figure below. Explain the model composition, how it works, and why in your opinion it is able to achieve such a high performance? 224 x 224 x 3 224 x 224 x 64 112 x 112 x 128 56 x 56 x 256 7 x 7 x 512 28 x 28 x 512 14 x 14 x 512 1 x 1 x 4096 1 x 1 x 1000 convolution+ReLU max pooling fully nected+ReLU softmax 0000
Chapter1: Financial Statements And Business Decisions
Section: Chapter Questions
Problem 1Q
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Question
![[10 points] VGG16 is a convolutional neural network model proposed by K.
Simonya and A. Zisserman from the University of Oxford. The model achieves
92.7% top-5 test accuracy in ImageNet. VGG16 is shown in the figure below.
Explain the model composition, how it works, and why in your opinion it is able to
achieve such a high performance?
224 x 224 x 3 224 x 224 x 64
112 x 112 x 128
56 x 56 x 256
7 x 7 x 512
28 x 28 x 512
14 x 14 x 512
1 x 1 x 4096 1 x 1 x 1000
convolution+ReLU
max pooling
fully nected+ReLU
softmax
0000](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe29803dc-f700-4505-aaa0-228902783314%2F47c96e59-e476-46db-a60c-ecab3ebeec48%2Fqfjeoo8_processed.jpeg&w=3840&q=75)
Transcribed Image Text:[10 points] VGG16 is a convolutional neural network model proposed by K.
Simonya and A. Zisserman from the University of Oxford. The model achieves
92.7% top-5 test accuracy in ImageNet. VGG16 is shown in the figure below.
Explain the model composition, how it works, and why in your opinion it is able to
achieve such a high performance?
224 x 224 x 3 224 x 224 x 64
112 x 112 x 128
56 x 56 x 256
7 x 7 x 512
28 x 28 x 512
14 x 14 x 512
1 x 1 x 4096 1 x 1 x 1000
convolution+ReLU
max pooling
fully nected+ReLU
softmax
0000
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