Micro Neural-Controller for Optical Character Recognition
Abstract
This paper presents a Micro-Neural Controller (MNC) for Optical Character Recognition (OCR). The controller consists of both a multilayered feedforward Artificial Neural Network (ANN) and a von Neumann-type microcontroller. The ANN is supervised and trained using back-propagation. The role of the ANN is to perform character recognition while the microcontroller coordinates the data transfer between the network and the user. The results show that the network recognizes the patterns effectively and the microcontroller is able to execute a demonstration program.
Citation
Lim, Ker-chin and Ortega-Sanchez, Cesar. 2006. : Micro Neural-Controller for Optical Character Recognition, in ., Murdoch University (ed), Postgraduate Electrical Engineering and Computing Symposium, Nov 07 2006, pp. 145-148. Murdoch University, WA: Murdoch University.
Source Title
Procs. 7th Postgraduate Electrical Engineering and Computing Symposium
Faculty
Faculty of Engineering and Computing
Department of Electrical and Computer Engineering
Division of Engineering, Science and Computing
Collection
Related items
Showing items related by title, author, creator and subject.
-
Lau, M.; Lim, Hann; Gopalai, A. (2015)Traffic sign recognition system is an important subsystem in advanced driver assistance systems (ADAS) that assisting a driver to detect a critical driving scenario and subsequently making an immediate decision. Recently, ...
-
Zuo, L.; Wan, X.; Liu, Jian (2016)© 2016 IEEE. In recent years, research on language modeling for speech recognition has increasingly focused on the application of neural networks. However, the performance of neural network language models strongly depends ...
-
Ang, L.; Lim, Hann; Seng, K.; Chin, S. (2009)This chapter presents a new face recognition system comprising of feature extraction and the Lyapunov theory-based neural network. It first gives the definition of face recognition which can be broadly divided into (i) ...