CS488 Update

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In the past week, I worked on modifying my diagram and finished generating results. I also tried to draw meaningful insights from the validation results. After chatting with Xunfei, I finalized my poster and thought about elements to add to … Read More

CS488 – Update

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I couldn’t do much due to comps, but collected all information from participants to conduct the validation process. I also ran their results on my software and recorded the results. This week, I will work on extracting relevant reviews from … Read More

CS 488 – Week 10

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Having implemented my first two models, I started working on the front end of my project for the user to interact with. This upcoming week I will keep working on the frontend as well as the poster and the paper. 

CS 488 – Week 9

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This past week I worked on my other model that uses both engaging/readable and non-engaging/readable advertisements, I found that this model does not perform well because of the lack of parallel data and sentence structures between the two different sentences. … Read More

CS488 – Elevator Pitch

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Information informs our entire lives. Information shapes public opinion which shapes things like public policy, elections, the health and safety of the public, and more. No one is above the harm that can come from misinformation, which is why we … Read More

Elevator Pitch

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My senior project is to develop a technology that provides higher performance and security for target applications. It is called unikernel which is an optimized library operating system. Unikernel consists of the minimum set of components that a target application … Read More

CS 488 – Week 6

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— Elevator Pitch —  My project aims to use a sequence to sequence encoder-decoder model to make text-based advertisements more engaging and readable. This will help businesses get an edge over their competitors by attracting new customers as well as retaining … Read More

CS 488 – Week 6

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This week I started working on writing the first draft of the paper. The models seemed to run probably when I tried to test with the small data set. However the accuracy was not what I wanted since there were … Read More

CS 488 – Week 5

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This week, I focus on the writing parts including the outline for the capstone paper. I also start implementing some neural network models for the image data set such as MobileNet and EfficientNet. I will try to test the model … Read More

CS 488 – Week 5

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I finished writing my initial model and have trained it using a small sample dataset. The accuracy of my initial model is quite bad. I am currently researching how I can modify and improve the accuracy of my model as well as downloading … Read More

CS 488 – Week 4

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Last week I worked on collecting and preprocessing the data using Groupon API. I also started learning about and implementing my autoencoder model. So far the obstacle has been the learning curve but I have been extensively reading about neural … Read More

CS 488 – Week 4

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This week, I started the data preprocess for my image data. The steps include, resizing, cropping, normalizing and lastly change to tensor value so that it can be fit in a neural network. For the numerical data set, I started … Read More

CS 488 – Week 3

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This week, I tried to implement some models and was hoping to get it on our Layout server with GPUs. However, the system admins were still working on that and I could not ssh to the server. Therefore, I created … Read More

CS 488 – Week 2

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This week I have looked at some papers of most recent models for classifying images to build for my dataset. I encountered some challenges while reading those papers since there were terms that were hard to understand. Next week, I … Read More

CSS 488 – Week 2

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Due to a lack of available usable datasets, after talking to my advisor and instructor I decided to modify my project to focus on readability and sentiment instead. I researched papers on readability and sentiment this last week and have … Read More

CS 488 – Week 2 – Updates

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I decided to change my modeling method to neural networks. I have read a paper called Text-Independent Speaker Verification Using 3D Convolutional Neural Networks and checked their resources on GitHub. I tried to run their demo but required packages couldn’t … Read More

CS 488 – Week 1

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I go through the project again because it has been a while since I had CS 388 last Spring. I downloaded the data set and started doing some data manipulation and preprocessing. I will start looking at the models for … Read More

Week 9

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During my weakly meeting with Igor, he brought to my attention a better way to increment the ranking algorithm. In the first round, a certain number of image processing techniques will be applied to the original image and the top … Read More

Week 8

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In the past few weeks I have settled on my topic being exploring gender bias on a website using a combination of computational linguistics and quantitative analysis. After writing my literature review on work that explored a variety of sites, … Read More

Week 8

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While preparing my diagram for the quiz, I got a much better conceptual understanding of what I want my project to look like. I have also found nice papers this week. I started thinking of a few different image processing … Read More

CS388 – Week 7 – Update

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I finalized my proposal to “Applying Voiceprint Recognition Technology to Identity Verification”. The keywords are voice recognition, voiceprint, feature extraction, voice detection, voice verification. The difficulty I might encounter is that there may be background noise in the voice input. If … Read More

Week 6

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I am going with the auto-image processing for food. I have been looking more into the literature, and there is limited literature that deals with making food look better, and they are all relatively recent publications. However, there is literature … Read More

Week 4

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After talking to Igor, I realized I could incorporate a food recommendation system to my food ordering app. After thinking some more, I realized the food recommender might actually be more interesting than the food ordering system.

CS388-Week3-Updates

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I am still exploring my new ideas. Idea 1 Title: AI Assistant for Safety Driving Description: My idea is to use facial recognition to detect fatigue driving or dangerous driving. A small camera will be placed in front of the … Read More

CS388 – Week 2 – Three Ideas

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First Idea: Credibility Analyzer Create a database of media of different opinions that are credible with truthful information. Using Machine Learning, find/develop an algorithm that when given a medium could accurately determine whether it is credible and truthful. Create an … Read More

Week 4 Update

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In past week, I have spent time doing research to find interesting papers that I think will be related to my ideas. For each of my ideas there are at least five papers to take a look on at thee … Read More

Weekly Update

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Read the CS papers help documents to understand how to read and understand the long papers. Finding difficulties in searching for papers directly related to my ideas. Read a couple of papers according to the instructions which helped understand the … Read More

Weekly Progress CS388 (2/15)

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For this week, I have been looking for research papers on the three topics that I have chose, specifically for the Text Categorization and the Air Quality Monitoring system. Two things I found out: – Air Quality Monitoring system:There have … Read More

Week 3 Update

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I have talked with Ajit about all three ideas and received some feedbacks and suggestion. Also, I have started finding research papers that are related to my ideas to read for next week.

Topic ideas

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Here are my ideas for topics! Another post with some cost analyses is coming soon! Topic Name: Real-time management using Augmented Reality  Topic Description: Examine the applications of Head-Mounted augmented reality displays such as HoloLens or Project Northstar in real-time … Read More

Week 1 Ideas

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Idea 1: Optical Character Recognition using Machine Learning Optical character recognition is not a completely new field of research. However, with the advance of today’s technology, we can apply machine learning to optical character recognition and therefore can recognize not … Read More