Classyfing Skin Cancer in Digital Images Using Convolutional Neural Network With Augmentation
ZEYHAN ALIYAH
Informasi Umum
Kode
20.04.1278
Klasifikasi
004 - Data processing, Computer science
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Computer Science
Dilihat
133 kali
Informasi Lainnya
Abstraksi
Skin cancer is a hazardous disease that can induces death if it is not taken care of immediately. The disease is hard to identified since the symptoms have similarities with other disease. An automatically classification system of skin cancer has been developed, but it still produced low accuracy. We use Convolutional Neural Network to enhance the accuracy of the classification. There are 2 main scenarios conducted in this research using HAM10000 dataset which has 7 classes. We compared ResNet and VGGNet architectures and obtained ResNet50 with augmentation as the best model with the accuracy of 99% and 99% macro avg.
Keywords: Convolutional neural network, classification, digital image, skin cancer
- CCH1A4 - DASAR ALGORITMA DAN PEMROGRAMAN
- CCH3F3 - KECERDASAN BUATAN
- CSH3L3 - PEMBELAJARAN MESIN
- CCH1D4 - STRUKTUR DATA
- CII2B4 - STRUKTUR DATA
- CII3C3 - PEMBELAJARAN MESIN
- CPI2B4 - STRUKTUR DATA
Koleksi & Sirkulasi
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Pengarang
| Nama | ZEYHAN ALIYAH |
| Jenis | Perorangan |
| Penyunting | ANDITYA ARIFIANTO, FEBRYANTI STHEVANIE |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Ilmu Komputasi |
| Kota | Bandung |
| Tahun | 2020 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
