Wearable Device for Malaysian Ringgit Banknotes Recognition Based on Embedded Decision Tree Classifier
Velázquez, R., Wearable Assistive Devices for the Blind, in Wearable and Autonomous Biomedical Devices and Systems for Smart Environment: Issues and Characterization, A. Lay-Ekuakille and S.C. Mukhopadhyay, Editors. 2010, Springer Berlin Heidelberg: Berlin, Heidelberg. p. 331-349.
Mohamed, A., M.I. Ishak, and N. Buniyamin. Development of a Malaysian Currency Note Recognizer for the Vision Impaired. in 2012 Spring Congress on Engineering and Technology. 2012.
Hinwood, A., et al., Bank note recognition for the vision impaired. 2006(0158-9938 (Print)).
Wickramasinghe, K. and D.D. Silva. Bank notes recognition device for Sri Lankan vision impaired community. in 2013 8th International Conference on Computer Science & Education. 2013.
Semary, N.A., et al. Currency recognition system for visually impaired: Egyptian banknote as a study case. in 2015 5th International Conference on Information & Communication Technology and Accessibility (ICTA). 2015.
Sarfraz, M., An Intelligent Paper Currency Recognition System. Procedia Computer Science, 2015. 65(Supplement C): p. 538-545.
Ahangaryan, F.P., T. Mohammadpour, and A. Kianisarkaleh. Persian Banknote Recognition Using Wavelet and Neural Network. in 2012 International Conference on Computer Science and Electronics Engineering. 2012.
Solymár, Z., et al. Banknote recognition for visually impaired. in 2011 20th European Conference on Circuit Theory and Design (ECCTD). 2011.
Suganya, K. and G. Ba;akrishnan. Banknote Recognition System for Visually Impaired. in International Journal of Advanced Research Trends in Engineering and Technology (IJARTET) 2015. Department of Computer Science and Engineering Indra Ganesan College of Engineering, Trichy.
García-Lamont, F., et al., Classification of Mexican Paper Currency Denomination by Extracting Their Discriminative Colors, in Advances in Soft Computing and Its Applications: 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, Mexico City, Mexico, November 24-30, 2013, Proceedings, Part II, F. Castro, A. Gelbukh, and M. González, Editors. 2013, Springer Berlin Heidelberg: Berlin, Heidelberg. p. 403-412.
Brassai, S.T., L. Bako, and L. Losonczi, Assistive Technologies for Visually Impaired People. Acta Universitatis Sapientiae, Electrical and Mechanical Engineering, 2011. 3: p. 39-50.
Inc, T.A.O.S., TCS3472 Color Light-to-Digital Converter with IR Filter, T.L. Company, Editor. 2012: Texas. p. 1-26.
Yi, C., et al., Finding Objects for Assisting Blind People. Network modeling and analysis in health informatics and bioinformatics, 2013. 2(2): p. 71-79.
Lanigan, P.E., et al. Trinetra: Assistive Technologies for Grocery Shopping for the Blind. in 2006 10th IEEE International Symposium on Wearable Computers. 2006.
Karacs, K., R. Wagner, and T. Roska, Bionic Eyeglass: Personal Navigation System for Visually Impaired People, in Focal-Plane Sensor-Processor Chips, Á. Zarándy, Editor. 2011, Springer New York: New York, NY. p. 227-244.
Buchs, G., S. Maidenbaum, and A. Amedi, Obstacle Identification and Avoidance Using the ‘EyeCane’: a Tactile Sensory Substitution Device for Blind Individuals, in Haptics: Neuroscience, Devices, Modeling, and Applications: 9th International Conference, EuroHaptics 2014, Versailles, France, June 24-26, 2014, Proceedings, Part II, M. Auvray and C. Duriez, Editors. 2014, Springer Berlin Heidelberg: Berlin, Heidelberg. p. 96-103.
De Ville, B., Decision Trees for Business Intelligence and Data Mining: Using SAS Enterprise Miner. 2006: SAS Institute.
Rastogi, R. and K. Shim, PUBLIC: A Decision Tree Classifier that Integrates Building and Pruning. Data Mining and Knowledge Discovery, 2000. 4(4): p. 315-344.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.