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Computer Vision and Graphics · Artificial Intelligence
This section demonstrates that I have met the graduate requirement of Computer Science Meng degree. I will demonstrate my core knowledge for following three different fields.
· Computer Vision and Graphics
· Artificial Intelligence
· Software Engineering
In computer vision and graphics field, the major concept is to use open graphic library to write a program that can show the graphics. To fully understand the major concepts, there are several things need to know and I also have learned all of them which shows below.
1. Texture mapping: I can use different texture to map on different objects that can make the objects have different outlooks. (figure 1)
2. Lighting: I can set up points light, spotlight, and directional light to light where I want in a graphics. (figure 2)
3. Animation: I can animate the objects I set up by using time function.
4. Shaders: using GPU to show the 3D objects on the screen which is much faster.
5. Transparency: I can adjust the parameters in transparency function to transparent the objects.
Figure 1 using different texture to create different planets Figure 2 using different lighting mode to light the objects
How we can use those techniques to generate a graph we want is the main knowledge I learned in this field. Let me explain you how we can do this by building a solar system. First, you need to use texture to map the picture of each planet on the object you create. Second, using lighting to set up the light point at the location where sun is. After that, adding the animation to let every planet do revolution and rotation. Now, you can get a rough solar system.
In Artificial Intelligence field, the major concepts are the different models of machine learning and deep learning. In this field, the main idea is to teach computer to do things like human, so we will use a lot of data to train the machine with different models. After training, we can let the machine do anything we want. For example, the image classification, house price prediction, etc. There are a lot of different models including SVM, Random Forest, CNN, LSTM, and so on that can use to train the data. In general, the basic ideas of what the models do is to use a lot of data features to make prediction or generate the result by computation. For example, imaging that you would like to predict the price of a house, and you must have a lot of features of that house like the size of the house, the number of rooms in the house, etc. I can use that information as inputs to the model, and I can get the output until I achieve certain accuracy after computing multiple times. As you can see, in figure 3, it shows an CNN model with the inputs of image information and generate the outputs after computation. Figure 3 CNN model implementation
In Software engineering field, the main concept is the software developing methods. Most of the software projects need a group of people cooperate together, so there are a lot of software developing methods come up including waterfall and agile.
Waterfall is a method that uses in the software with high risky and security that cannot modify frequently. During the developing period, everything needs to be considered rigorously because we will not go back to previous step to modify the software application. For instance, the autopilot of airplane that we can’t make any mistakes on it due to human’s safety.
On the contrast, agile is a totally different software developing method. Developers will meet up frequently, and the application can be modified frequently depending on users’ requirements. Hence, members in the team will do self-examination frequently and make adjustment to let all working become more efficient. I have implemented this method to do team project, so I realize what each position should do in this method and what things need to be done in each sprint of the agile developing method.
The concepts I mentioned above show that I have the core knowledge in these three fields.