Fashion Type Classification for E-Commerce using Semantic Segmentation

MUHAMMAD FARHAN AUDIANTO

Informasi Dasar

51 kali
23.04.807
C
Karya Ilmiah - Skripsi (S1) - Reference

The Internet has become a big thing nowadays. The current growth of infrastructure allows more people to reach the Internet. The Internet has dramatically influenced the e-commerce market. E-commerce has grown significantly, and many new e-commerce sites, including Instagram with their Instagram Shopping, have started appearing. In Instagram Shopping, there is no label for the product, which is essential in e-commerce. This project is about labeling the fashion image using semantic segmentation. The method that was used is U-Net. In this project, we trained the model with 2 different epochs, 10 and 50. The mean IoU on 10 epoch model is 0.044, and 50 epoch model, is 0.092. Moreover, the weighted F1-Score on 10 epoch model is 0.760 and 50 epoch model 0.819. Subsequently, the label output result was filtered with a pixel-count threshold to reduce the noisy label on the output.

Subjek

IMAGE PROCESSING
 

Katalog

Fashion Type Classification for E-Commerce using Semantic Segmentation
 
 
Indonesia

Sirkulasi

Rp. 0
Rp. 0
Tidak

Pengarang

MUHAMMAD FARHAN AUDIANTO
Perorangan
Ema Rachmawati, Mahmud Dwi Sulistyo
 

Penerbit

Universitas Telkom, S1 Informatika
Bandung
2023

Koleksi

Kompetensi

 

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