Offline Handwriting Recognition Using Feedforward Neural Network

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Rosalina 1,* R.B. Wahyu 1

1. President University, Faculty of Computing, Bekasi, Indonesia

* Corresponding author.


Received: 30 Mar. 2017 / Revised: 11 May 2017 / Accepted: 8 Jun. 2017 / Published: 8 Sep. 2017

Index Terms

Handwriting recognition, feedforward neural netwok, form


Many business especially Banks’s services are expanding to include services directed not only to corporate customers but also to individual customer. Furthermore, by the increment of those services, many individual applications to be processed also increases as well. Facing an immense moment, in which requiring more improvements in how it should manage or maintain its applications, some systems or procedures must be improved to match currently increasing customers’ applications. Prior to the improvements, many application forms are filled, input to machine and even to be processed and approved manually. Until recently, application fulfillment processes consists of manual information filling by applicants in an application request paper and later to be re-input by electronic data processing staff which is actually redundant. Aware of such situation, this paper proposes and idea to reduce input processes in an integrated business system by utilizing character recognition system.

Cite This Paper

Rosalina, R.B. Wahyu, "Offline Handwriting Recognition Using Feedforward Neural Network", International Journal of Information Technology and Computer Science(IJITCS), Vol.9, No.9, pp.11-17, 2017. DOI:10.5815/ijitcs.2017.09.02


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