Suppose you are designing a deep learning architecture to solve an object detection problem, where there areN numbers of objects and each object has M number of images. If the resolution of each image is 227 x 227 x 3, then answer the following questions: (a) Write down the name of the layers of your deep learning architecture including parameters dimension. (b) How many convolution layers will you use in your deep learning model and why? (c) Is it a good idea to use multiple fully connected layers? Motivate your answer
Suppose you are designing a deep learning architecture to solve an object detection problem, where there areN numbers of objects and each object has M number of images. If the resolution of each image is 227 x 227 x 3, then answer the following questions: (a) Write down the name of the layers of your deep learning architecture including parameters dimension. (b) How many convolution layers will you use in your deep learning model and why? (c) Is it a good idea to use multiple fully connected layers? Motivate your answer
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Transcribed Image Text:Suppose you are designing a deep learning
architecture to solve an object detection
problem, where there areN numbers of
objects and each object has M number of
images. If the resolution of each image is
227 x 227 x 3, then answer the following
questions:
(a) Write down the name of the layers of
your deep learning architecture including
parameters dimension.
(b) How many convolution layers will you
use in your deep learning model and why?
(c) Is it a good idea to use multiple fully
connected layers? Motivate your answer
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