NPTEL Deep Learning Week 11 Assignment Answers 2025
1.
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2.
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3. What are the different challenges one face while creating a facial recognition system?
a. Different illumination condition
b. Different pose and orientation of face images
c. Limited dataset for training
d. All of the abov
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4. Fully Connected Convolutional network or FCN became one of the major successful network
architectures. Can you identify what are the advantages of FCN which makes it a successful
architecture for semantic segmentation?
a. Larger Receptive Field
b. Mixing of global feature
c. Lesser computation required
d. All of the above
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5.
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6. What could be thought as disadvantage of Fully Convolutional neural network for semantic
segmentation addressed by other researchers?
a. It has a fixed receptive field, so the object with lesser size than the receptive filed will be missed by the network.
b. Down Sampling the image dimension over the depth makes the feature map sparse.
c. It requires lot of computation.
d. None of the above
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9. In FaceNet, why the L2 normalization layer is used?
a. To constrain the embedding function in a d-dimensional hyper-sphere.
b. For regularization of weight vector, i.e. L2 regularization.
c. For getting a sparse embedding function.
d. None of the above.
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10. What is the use of Skip Connection in image denoising networks?
a. Helping de-convolution layer to recover an improved clean version of image.
b. Back propagating the gradient to bottom layers, which makes the training easy.
c. To create the direct path between convolution layer and the corresponding mirror de-convolution layer.
d. All of the above.
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