Snakebite Images Classification Using Random Forest Classifier
ALIFIANDO DESTARA YUSUF
Informasi Umum
Kode
19.04.3634
Klasifikasi
621.367 - Technological photography and photo-optics, Spectrography, Stroboscopic photography, Image processing, Optical data processing
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Image Processing
Dilihat
286 kali
Informasi Lainnya
Abstraksi
As classification system continuously develop and improve, it is becoming more available to everyone. This leads to the increasing popularity of classification system and the increase of classification system usage in every field. The example of classification system implementations are face recognition, spam detection and image recognition. This work classifies snakebite images using random forest classifier based on image’s shape, texture, and color feature descriptor. Random forest classifier is used as it is supposed to have a good performance when it comes to handle a small amount of data. The final model yields f1 score of 100% with 75% 4-fold cross validation accuracy. The dataset is contained of 20 snakebite images and divided into 16 train data and 4 test data.
Keywords: Image Classification, Random Forest Classifier, Snakebite, Feature Descriptor, Classification System
Koleksi & Sirkulasi
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Pengarang
| Nama | ALIFIANDO DESTARA YUSUF |
| Jenis | Perorangan |
| Penyunting | Adiwijaya, Dody Qori Utama |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Informatika |
| Kota | Bandung |
| Tahun | 2019 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
