IJAIT (International Journal of Applied Information Technology)
Vol 05 No 01 (May 2021)

Prototyping Feed-Forward Artificial Neural Network on Spartan 3S1000 FPGA for Blood Type Classification

Rizki Ardianto Priramadhi (Dept. of Electrical Engineering, Telkom University, Indonesia)
Denny Darlis (Diploma of Telecommunication Technology, Telkom University, Indonesia)



Article Info

Publish Date
08 Jan 2022

Abstract

In this research, a Feed-Forward Artificial Neural Network design was implemented on Xilinx Spartan 3S1000 Field Programable Gate Array using XSA-3S Board and prototyped blood type classification device. This research uses blood sample images as a system input. The system was built using VHSIC Hardware Description Language to describe the feed-forward propagation with a backpropagation neural network algorithm. We use three layers for the feed-forward ANN design with two hidden layers. The hidden layer designed has two neurons. In this study, the accuracy of detection obtained for four-type blood image resolutions results from 86%-92%, respectively.

Copyrights © 2021






Journal Info

Abbrev

ijait

Publisher

Subject

Computer Science & IT

Description

International Journal of Applied Information Technology covers a broad range of research topics in information technology. The topics include, but are not limited to avionics, bio medical instrumentation, biometric, computer network design, cryptography, data compression, digital signal processing, ...