A produce dealer has a warehouse that stores a variety of fruits. He wants a machine capable of sorting the fruit according to the type. There is a conveyor belt on which the fruit is loaded. It is then passed through a set of sensors which measure 3 properties of the fruit: shape, texture, and weight. The sensor system is somehow rather primitive:Shape sensor: -1 if the fruit is round and 1 if it is more ellipticalTexture sensor: -1 if the surface is smooth, 1 if it is roughWeight sensor: -1 if the fruit is > 500g, 1 if is < 500gThe sensor output will then be input to a Neural Networks based classifying system. As an AI Engineer you are supposed to design (draw the architecture and determine the optimal weight Wand bias b) a simple neural network (could be a single perceptron) that can be used to recognize the fruit so that it can be directed to the correct storage bin. As a startup case, the simple network will only be used for two type of fruit i.e. banana and apple. Employ initial weight W = (0.5 -1.0 -0.5) and b = 0.5. Datasets from the sensor are as follows: banana = (-1, 1, -1); apple = (1, 1, -1).

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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

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A produce dealer has a warehouse that stores a variety of fruits. He wants a machine capable of sorting the fruit according to the type. There is a conveyor belt on which the fruit is loaded. It is then passed through a set of sensors which measure 3 properties of the fruit: shape, texture, and weight. The sensor system is somehow rather primitive:

Shape sensor: -1 if the fruit is round and 1 if it is more elliptical
Texture sensor: -1 if the surface is smooth, 1 if it is rough
Weight sensor: -1 if the fruit is > 500g, 1 if is < 500g

The sensor output will then be input to a Neural Networks based classifying system. As an AI Engineer you are supposed to design (draw the architecture and determine the optimal weight Wand bias b) a simple neural network (could be a single perceptron) that can be used to recognize the fruit so that it can be directed to the correct storage bin. As a startup case, the simple network will only be used for two type of fruit i.e. banana and apple. Employ initial weight W = (0.5 -1.0 -0.5) and b = 0.5. Datasets from the sensor are as follows: banana = (-1, 1, -1); apple = (1, 1, -1).

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