Which is false?Group of answer choicesOutput of a layer in the residual network is the normal output (i.e, what’s produced after applying a filter and an activation function) + the layers input.Output of a layer in the dense network is the normal output (i.e, what’s produced after applying a filter and an activation function) + the layers input.Output of layer 𝑙 in the dense network will be one of the inputs for layers 𝑖∈(𝑙+1,𝐿) where 𝐿 is the total number of layers.A problem of convolution network is that some features may get extracted earlier in the network, but could be useful later on. However, it is hard to keep track of previous non-modified outputs.

Which statement is true?Group of answer choicesConvolutional neural networks tend to only have 10 layers.If the feature response value is large, then that portion of the image does not look like the filter.The convolutional kernel can only take all-positive or all-negative values at a time.If there is no pattern to find, the feature response is a weighted average with the result of blurring the image.

Which ones of the following statements on Residual Networks are true? (Check all that apply.)

Which of the following are true about Depthwise-separable convolutions? (Choose all that apply)

Suppose we have a convolutional neural network with a 5x5x1 input volume, followed by one convolutional layer with 5 filters that have a 2x2x1 receptive field, followed by one fully connected output layer with 5 neurons.  How many weights does the network have in total?A model answer for this question will be released towards the end of the week. Correct answer  430   2500 You Answered  2485   805   530

Question 7Which of the following are true about the inception Network? (Check all that apply)