Author: Haroon Khalil
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Digital image representation
A digital image is a function f(X, Y), where X, Y coordinates are discontinuous in spatial and brightness. It is represented by a set of numbers that can be stored and controlled by a digital computer. It is formed by combing small bits of data called pixels. These pixels are stored in a computer, so…
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Binary image
Binary image pixel contains two grey level values. Grey level “0” constitutes black and grey level “1” constitutes white color. The pixel value is stored in 1-bit format. Binary images are repeatedly produced by a method called thresholding. This thresholding technique is applied to color images or greyscale images, and from these two we obtain…
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Color image
A color image is a two-dimensional image usually represented by three different colors per pixel. It constitutes 24 bits per image. These 24 bits are divided into 3 equal parts, each of 8 bits which give information of intensity values of red, green and blue with 8 bits of red, 8 bits of green and…
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Greyscale image
The greyscale images consist of 256 grey tones of colors. The main feature of the greyscale image is the equal distribution of colors red, green and blue. It carries only intensity information of individual pixels as a single sample and is composed of a wide range of shades. It is also called monochrome image. The…
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Introduction
An image conveys information. It consists of prime elements called pixels, where each pixel is represented by some value, with the function of two coordinates X and Y in mathematical representation. An image consists of organized pixels in rows and columns.
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Result and conclusion
Here we have used three methods: We have used the parameters of mean absolute error (MAE) and mean square error (MSE) and compared different models. We can see from the given bar graph that a good result is shown by deep neural network and also the MAE and MSE have lowest value in the represented…
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Case study
We know that agriculture is an important part of gross domestic product. This project cussed in the advantage of insurance companies so they have efficient insurance coverage. In this project, we have taken two test datasets. One is 2CSV files and another is image dataset. CSV file has lots of features like temperature, humanity, pressure…
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A century of crop protection
Since this chapter is related to forecasting, we must have an idea of the development of agricultural stages so as to link these stages with machine learning. During the past 100 years, there was an indifference in the technology and most of the development is seen in the last 5 years (Figure 5.9). Hundred years ago About…
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Uses of machine learning in agriculture
AI technique is used in different sectors from home to offices, and presently in agriculture also. In the agricultural field, the use of machine learning increases the productivity and quality of the crop. Retailers The seed retailers use this agriculture technology to churn the data to create better crops. While the pest control companies are…
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Reinforcement machine learning algorithm
Here, the agent learns the property of behaviors to the environment by the performance of the act and checks the results of action. Application of machine learning in different sectors: