Anaslisis Penggunan Super Image Resolution Dengan Menggunakan EDSR dan WDSR Pada Sel Manusia
Abstract
Teknologi digital berkembang secara cepat dan masif. Salah satunya pada proses pengamatan sel pada manusia. Teknologi tingkat tinggi yang digunakan untuk proses tersebut adalah menggunakan PET Scan. Namun teknologi tersebut masih memiliki kekurangan, yaitu buruknya citra yang dihasilkan. Penelitian ini berfungsi untuk memperbaiki permasalahan tersebut. Dengan menjadikan output dari PET Scan sebagai data masukan (dataset) ke dalam sebuah model jaringan super-resolution, yaitu model Enhanced Deep Residual Networks for Single Image Super-Resolution (EDSR) dan Wide Activation for Efficient and Accurate Image Super-Resolution (WDSR). Tipe dataset yang digunakan adalah PET Y-90. Model kemudian ditraining untuk melihat seberapa baik model bekerja pada dataset. Proses training dilakukan dengan steps sebanyak 300.000 kali dan batch size 16, serta Scalling dari kedua model adalah 4. Hasil dari proses training akan dianalisis untuk melihat efektifitas perbaikan citra yang dihasilkan model. Dengan membandingkan PSNR dan SSIM yang dihasilkan dapat melihat kualitas citra yang dihasilkan oleh kedua model . Hasil PSNR dari EDSR dan WDSR masing-masing sebesar … dB dan … dB, serta SSIM sebesar … dan … . Setelah dataset di training, citra dengan kualitas rendah dari dataset dapat diubah menjadi citra dengan kualitas Super Resolution.
Kata kunci : EDSR,WDSR,Super-Resolution,Deep Learning
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