Difference between revisions of "F21-STAT 441/841 CM 763-Proposal"

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(Created page with "Use this format (Don’t remove Project 0) Project # 0 Group members: Last name, First name Last name, First name Last name, First name Last name, First name Title: Maki...")
 
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Description: We use paper cups to make a string phone and talk with friends while learning about sound waves with this science project. (Explain your project in one or two paragraphs).
 
Description: We use paper cups to make a string phone and talk with friends while learning about sound waves with this science project. (Explain your project in one or two paragraphs).
  
Project # 1 Group members:
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'''Project # 1 Group members:'''
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Song, Quinn
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Loh, William
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Bai, Junyue
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Choi, Phoebe
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'''Title:''' APTOS 2019 Blindness Detection
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'''Description:'''
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Our team chose the APTOS 2019 Blindness Detection Challenge from Kaggle. The goal of this challenge is to build a machine learning model that detects diabetic retinopathy by screening retina images.
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Millions of people suffer from diabetic retinopathy, the leading cause of blindness among working-aged adults. It is caused by damage to the blood vessels of the light-sensitive tissue at the back of the eye (retina). In rural areas where medical screening is difficult to conduct, it is challenging to detect the disease efficiently. Aravind Eye Hospital hopes to utilize machine learning techniques to gain the ability to automatically screen images for disease and provide information on how severe the condition may be.
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Our team plans to solve this problem by applying our knowledge in image processing and classification.

Revision as of 12:11, 6 October 2020

Use this format (Don’t remove Project 0)

Project # 0 Group members:

Last name, First name

Last name, First name

Last name, First name

Last name, First name

Title: Making a String Telephone

Description: We use paper cups to make a string phone and talk with friends while learning about sound waves with this science project. (Explain your project in one or two paragraphs).


Project # 1 Group members:

Song, Quinn

Loh, William

Bai, Junyue

Choi, Phoebe

Title: APTOS 2019 Blindness Detection

Description:

Our team chose the APTOS 2019 Blindness Detection Challenge from Kaggle. The goal of this challenge is to build a machine learning model that detects diabetic retinopathy by screening retina images. Millions of people suffer from diabetic retinopathy, the leading cause of blindness among working-aged adults. It is caused by damage to the blood vessels of the light-sensitive tissue at the back of the eye (retina). In rural areas where medical screening is difficult to conduct, it is challenging to detect the disease efficiently. Aravind Eye Hospital hopes to utilize machine learning techniques to gain the ability to automatically screen images for disease and provide information on how severe the condition may be. Our team plans to solve this problem by applying our knowledge in image processing and classification.