References
- Jayadevan R, Kolhe SR, Patil PM, Pal U (2011) Offline recognition of Devanagari script: a survey. IEEE Trans Syst Man Cybern Part C Appl Rev. ISSN 1094-6977
- J. Pradeep, E. Srinivasan and S. Himavathi, “Neural network based handwritten character recognition system without feature extraction,” 2011 International Conference on Computer, Communication and Electrical Technology (ICCCET), Tamil nadu, 2011. 40–44.
- Manoj Sachan (2015): Offline Gurumukhi script recognition using Knowledge Based Approach & MLP neural network “International conference on signal processing, computing and control”.
- Ved Prakash Agnihotri (2012): Offline Handwritten Devnagri script recognitiosn: MECS/ijitcs, 2012.
- Rafael C. Gonzalez, Richard E Woods, Steven L. Eddie, Digital Image Processing using MATLAB, pearson education, South Asia 2004.
- Sahu N, Raman NK (2013) An efficient handwritten Devanagari characters recognition system using neural network. In: International multi-conference on automation, computing communication, control and compressed sensing (iMac4s), IEEE. ISBN 978-1-4673-5089-1
- Pradeep, J., E. Srinivasan, and S. Himavathi. “Performance analysis of hybrid feature extraction technique for recognizing English hand-written characters”, 2012 World Congress on Information and Communication Technologies, 2012.
- Obaidullah SM, Monadal A, Roy K (2014) Structural feature based approach for script identification from printed Indian document. In IEEE international conference on signal processing and integrated networks.
- Basu S, Das N, Sarkar R, Kundu M, Nasipuri M, Basu DK (2010) A novel framework for automatic sorting of postal documents with multi-script address blocks. Pattern Recognit 43(10):3507–3521. doi: 10.1016/j.patcog.2010.05.018
- Hassan E, Chaudhury S, Yadav N, Kalra P, Gopal M (2014) Offline hand written input based identity determination using multi kernel feature combination. Pattern Recognit Lett 35:113–119. doi: 10.1016/j.patrec.2013.04.032
- Wshah S, Kumar G, Govidaraju V (2014) Statistical script independent word spotting in offline handwritten documents. Pattern Recognit 47(3):1039–1050. doi: 10.1016/j.patcog.2013.09.019
- M.M. Mehdi, A. Riaz,”Optimized word segmentation for the word based cursive handwriting recognition”, IEEE symposium on European modelling. 2013
- Pradeep, J., E. Srinivasan, and S. Himavathi. “Neural network based handwritten character recognition system without feature extraction”, 2011 International Conference on Computer Communication and Electrical Technology (ICCCET), 2011.
- Dhaka, Vijay Pal, and Manoj Kumar Sharma. “An efficient segmentation technique for Devanagari offline handwritten scripts using the Feedforward Neural Network”, Neural Computing and Applications, 2015.
- www.springerprofessional.de
- Poonia, Ramesh C., and Manish Kalra. “Bridging approaches to reduce the gap between classical and quantum computing”, Journal of Information and Optimization Sciences, 2016.
- Doherty, S.K.. “Experiment design considerations for non-linear system identification using neural networks”, Computers and Chemical Engineering, 19961115
- Pradeep, J., E. Srinivasan, and S. Himavathi. “Diagonal based feature extraction for handwritten character recognition system using neural network”, 2011 3rd International Conference on Electronics Computer Technology, 2011.