A Survey on using Neural Network based Algorithms for Hand Written Digit Recognition

Abstract

The detection and recognition of handwritten content is the process of converting non-intelligent information such as images into machine edit-able text. This research domain has become an active research area due to vast applications in a number of fields such as handwritten filing of forms or documents in banks, exam form filled by students, users’ authentication applications. Generally, the handwritten content recognition process consists of four steps: data preprocessing, segmentation, the feature¬ extraction and selection, application of supervised learning algorithms. In this paper, a detailed survey of existing techniques used for Hand Written Digit Recognition(HWDR) is carried out. This review is novel as it is focused on HWDR and also it only discusses the application of Neural Network (NN) and its modified algorithms. We discuss an overview of NN and different algorithms which have been adopted from NN. In addition, this research study presents a detailed survey of the use of NN and its variants for digit recognition. Each existing work, we elaborate its steps, novelty, use of dataset and advantages and limitations as well. Moreover, we present a Scientometric analysis of HWDR which presents top journals and sources of research content in this research domain. We also present research challenges and potential future work.

Authors and Affiliations

Muhammad Ramzan, Hikmat Ullah Khan, Shahid Mehmood Awan, Waseem Akhtar, Mahwish Ilyas, Ahsan Mahmood, Ammara Zamir

Keywords

Related Articles

A New Reliability Model for Evaluating Trustworthiness of Intelligent Agents in Vertical Handover 

Our previous works have proposed the deployment of mobile agents to assist vertical handover decisions in 4G. Adding a mobile agent in the 4G could lead to many advantages such as reduced consumption of network bandwidth...

Modeling and Analyzing Anycast and Geocast Routing in Wireless Mesh Networks

Wireless technology has become an essential part of this era’s human life and has the capability of connecting virtually to any place within the universe. A mesh network is a self healing wireless network, built through...

 A Modified Feistel Cipher Involving XOR Operation and Modular Arithmetic Inverse of a Key Matrix

 In this paper, we have developed a block cipher by modifying the Feistel cipher. In this, the plaintext is taken in the form of a pair of matrices. In one of the relations of encryption the plaintext is multiplied...

AATCT: Anonymously Authenticated Transmission on the Cloud with Traceability

In Cloud computing, anonymous authentication is an important service that must be available to users in the Cloud. Users have the right to remain anonymous as long as they behave honestly. However, in case a malicious be...

Computational Model for the Generalised Dispersion of Synovial Fluid

The metabolic function of synovial fluid is important to understand normal and abnormal synovial joint motion, especially if one seeks some leading causes of the degenerative joint disease. The concentration of hyaluroni...

Download PDF file
  • EP ID EP394221
  • DOI 10.14569/IJACSA.2018.090965
  • Views 119
  • Downloads 0

How To Cite

Muhammad Ramzan, Hikmat Ullah Khan, Shahid Mehmood Awan, Waseem Akhtar, Mahwish Ilyas, Ahsan Mahmood, Ammara Zamir (2018). A Survey on using Neural Network based Algorithms for Hand Written Digit Recognition. International Journal of Advanced Computer Science & Applications, 9(9), 519-528. https://europub.co.uk/articles/-A-394221