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# Tutor profile: Satabdi M.

Inactive
Satabdi M.
Current Researcher and former Adjunct lecturer
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## Questions

### Subject:MATLAB

TutorMe
Question:

how would you extract SURF feature from an color image and display with title?

Inactive
Satabdi M.

clear all; close all; img = imread('picture.jpg') % loading the image and reading the image gray_img = rgb2gray(img) % in MATLAB, surf feature is determined by detectSURFfeature %function and this function does not work with RGB or color images, it works for grayscale %image. so we are here converting the RGB image in grayscale features = detectSURFfeature(gray_img); % detecting SURF feature imshow(img); hold on;% showing the SURF features on image plot(features.selectStrongest(10));% showing 10 strongest points on the image

### Subject:Machine Learning

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Question:

if yesterday it rained in new jersey,what are the chances that it will rain today in new york?

Inactive
Satabdi M.

this is a very common type problem in both mathematics and computer science, as this problem can be solved by a machine learning concept called markov chain. the main purpose of machine learning is to make computer system learn from environment and data and take decision. to answer this problem, we will make a model. lets suppose that if it rains in new jersey then there is a 85% chance that it will rain in new york. so rain no rain 85% or 0.85 15% or 0.15 now again if it rained yesterday then there is a 45% chance of raining today. so if it rained yesterday then rain today no rain today 45% or 0.45 55% or 0.55 so if it rained yesterday in new jersey, then the chance that it will rain in new york today would be 0.85*0.45 = 0.3825 now this is a very basic example of solving machine learning problem with markov chain

### Subject:Computer Science (General)

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Question:

how to color a graph so that no two nodes have same color?

Inactive
Satabdi M.

this is a well known problem in case of both mathematics and computer science and known as graph coloring problem. in computer science , there are multiple ways to solve this issue. I am describing here one very basic and simple way. this is an algorithmic and psuedocode approach step 1: define adjacent nodes. such as node_1-> adjacent_node_0 etc step 2: define color of one node: node_0_color = red step 2: use if..else loop (in any language): if node_1 == adjacent_node_0 node_1_color = blue else node_1_color = node_0_color end step 3: do step 2 for all nodes in the graph. say there are 10 nodes in the graph, so by using for loop we can do for i = 1:10 calculate step 2 end at the end of this computation, you will see that all nodes are colored in different colors according to who is adjacent to each other.

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