PERBANDINGAN SEGMENTASI CITRA SENI TARI PENDET DAN SENI BELA DIRI PENCAK SILAT: PENDEKATAN DENGAN MULTIRES UNET - Sudirman, San; Setyanto, Arief; Kusnawi, Kusnawi (Jurnal Informatika dan Teknik Elektro Terapan, 2024)
This research compares image segmentation of the Pendet dance art and the Pencak Silat martial art using the MultiRes U-Net approach. Research methods include data collection, data pre-processing, data sharing, evaluation, and results. Evaluation results using the Dice coefficient, Jaccard index, and Mean Squared Error (MSE) metrics show the best scores for each dataset. The results of this research can increase understanding of these two arts and cultures through deeper visual analysis. The results of the image segmentation evaluation between Pendet dance and Pencak Silat martial arts using the MultiRes UNET approach show the best scores for Dice Coefficient (DC), Jaccard index, and Mean Squared Error (MSE). The best scores for the Pendet dance dataset are 98.47, 99.23, and 8.20E-04, while for the Pencak Silat dataset they are 88.29, 85.98, and 4.52E-04. Evaluation shows a good level of similarity between the segmented image and the original image.