In deep learning, is each feature map in a convolutional neural network extracted from input by a filter by a) using an affine transformation (i.e. biased convolution), a nonlinear activation and a pooling function? or b) by using an affine transformation (i.e. biased linear combination) and a pooling function?
In deep learning, is each feature map in a convolutional neural network extracted from input by a filter by a) using an affine transformation (i.e. biased convolution), a nonlinear activation and a pooling function? or b) by using an affine transformation (i.e. biased linear combination) and a pooling function?
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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In deep learning, is each feature map in a convolutional neural network extracted from input by a filter by a)
using an affine transformation (i.e. biased convolution), a nonlinear activation and a pooling function?
or b) by using an affine transformation (i.e. biased linear combination) and a pooling function?
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We have to explain that in deep learning, is each feature map in a convolutional neural network extracted from input by filter:
a) by using an affine transformation (i.e. biased convolution), a nonlinear activation and a pooling function?
or
b) by using an affine transformation (i.e. biased linear combination) and a pooling function?
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