WorksheetsImageNet Classification Reading PoW
Total questions: 10
Worksheet time: 4mins
Who is the primary author of the paper "ImageNet Classification with Deep Convolutional Neural Networks"
Ilya Sutskever
Alex Krizhevsky
Yann LeCun
Geoffrey Hinton
Which activation function did the AlextNet architecture use?
f(x) = tanh(x)
f(x) = (1 + e−x)−1
f(x) = max(0, x)
Choose the max pooling configuration used in the AlexNet architecture.
AlexNet uses a technique for reducing complex co-adaptation of neurons. Which of the following do they correspond to?
50% of all activations of the network were set to zero and also did not participate in backpropagation
Local response normalization
Combining prediction of different models
Dropout of 0.5
What type of neural network does AlextNet use?
Feedforward Neural Network
Perceptron
Convolutional Neural Network
Long Short Term Memory
What approaches of data augmentation did AlexNet opt?
Adding random crops of images, their rotations and flips in training
Light conditioning
Test time augmentation by prediction on corner and center patches of image
PCA color augmentation
On what did the AlextNet train on?
CPU
1 GPU
2 GPU
3 GPU
Which of the following statements are true based on the graph?
Implies the reason why the network uses saturating activations
The dotted lines corresponds to tanh and solid line to ReLU
Use of ReLU increased training speed of the network by six times
The dotted lines corresponds to ReLU and solid line to tanh
How many layers did AlexNet have?
8 convolutional layers
5 convolutional and 3 fully connected
8 fully connected layers
3 convolutional layers and 5 fully connected
Which of these do you consider the most crucial to the success of the architecture.
Down sampling images to fixed resolution of 256 x 256
ReLU non linearity
GPU cross parallelization
Normalization layer
Overlapping pooling
