Suppose we have the following CNN network: Input (225X225X3) ---> 5X5-filter (512-filters),Stride-2,padding-2 ---> 3X3-max-pooling,stride-1 ---> 3X3-filter (256-filters),Stride-2 ---> 2X2-max-pooling,stride-2 --->3X3-filter (128-filters),Stride-2,padding-0 --> 2X2 max-pooling,stride-2 ---> FullyConnected with 512 neurons ---> Fully Connected with 512 neurons ---> Fully Connected with 10 neurons.How many parameters do the Gradient-descent algorithm need to learn for this network? You may omitthe bias values from your calculations.

Suppose we have the following CNN network: Input (225X225X3) ---> 5X5-filter (512-filters),Stride- 2,padding-2 ---> 3X3-max-pooling,stride-1 ---> 3X3-filter (256-filters),Stride-2 ---> 2X2-max- pooling,stride-2 --->3X3-filter (128-filters),Stride-2,padding-0 --> 2X2 max-pooling,stride-2 ---> Fully

Suppose we have the following CNN network: Input (225X225X3) ---> 5X5-filter (512-filters),Stride- 2,padding-2 ---> 3X3-max-pooling,stride-1 ---> 3X3-filter (256-filters),Stride-2 ---> 2X2-max- pooling,stride-2 --->3X3-filter (128-filters),Stride-2,padding-0 --> 2X2 max-pooling,stride-2 ---> Fully

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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Concept explainers

Network transmission cabling

A network is a collection of devices connected by communication links. A device can be a computer or any instrument capable of sending and receiving data or information formed by other nodes toward the network. A channel that connects people or things is known as a network. It sends the data from one place to another. It is the basic concept of a computer, network, and data communications.

Question

Suppose we have the following CNN network: Input (225X225X3) ---> 5X5-filter (512-filters),Stride-
2,padding-2 ---> 3X3-max-pooling,stride-1 ---> 3X3-filter (256-filters),Stride-2 ---> 2X2-max-
pooling,stride-2 --->3X3-filter (128-filters),Stride-2,padding-0 --> 2X2 max-pooling,stride-2 ---> Fully
Connected with 512 neurons ---> Fully Connected with 512 neurons ---> Fully Connected with 10 neurons.
How many parameters do the Gradient-descent algorithm need to learn for this network? You may omit
the bias values from your calculations.

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