Term: Spring 2023
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Team ## Group 1
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Team members
- Wen Chen
- Chenyi Jiang
- Ashwathi Nair
- Hongju Ouyang
- Han Wang
- Zixun Zhang
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Project summary: In this project, we created a novel solution for image classification with noisy image labels. The team worked on building 2 models. In Model 1, we trained a CNN classification model with nosiy data. In Model II, we first built a label-cleaning model based on CNN that extracts visual features from images and used them to predict the actual labels, which are then passed through Model-I for image classification. In the evaluation section, we test all 3 models (baseline, model I and model II) and model 2 shows a great improvement in performance.
Contribution statement: (default) All team members contributed equally in all stages of this project. All team members approve our work presented in this GitHub repository including this contributions statement.
Following suggestions by RICH FITZJOHN (@richfitz). This folder is orgarnized as follows.
proj/
├── lib/
├── data/
├── doc/
├── figs/
└── output/
Please see each subfolder for a README file.