We are from team C22-PC381, and here is our project repository for Bangkit 2022 Capstone project. Our project combines technologies from machine learning, mobile development, and cloud computing to produce an application that can classify facial acne.
Member | Student ID | Learning Path | Role | Contacts |
---|---|---|---|---|
Ni Putu Eka Januartati | M2014K1365 | Machine Learning | Project Manager, Machine Learning Engineer | LinkedIn or Github |
Darwindra | M2012G1292 | Machine Learning | Machine Learning Engineer | LinkedIn or Github |
Farhan Rizqy Governilahnsyah | M2206K1907 | Machine Learning | Machine Learning Engineer | LinkedIn or Github |
Wawan Herwansyah | A2308F2654 | Mobile Development | Android Developer | LinkedIn or Github |
Ilham Arifin | C2122F1545 | Cloud Computing | Cloud Engineer | LinkedIn or Github |
Rifqi Hadi Firdaus | C2268G2300 | Cloud Computing | Cloud Engineer | LinkedIn or Github |
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Our project is built using Machine Learning Technology with Convolutional Neural Network algorithm. Here are the libraries used in our project:
We classify 3 types of acne disease, including:
- Blackhead
- Nodule
- Postule
After collected dataset from several source, we got total 356 dataset. The distribution is follows :
- Blackheads dataset : 96
- Nodules dataset : 130
- Pustules dataset : 130
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Download our android application at : https://bit.ly/tryacnetect
Or scan here:
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