@inproceedings{scholars6516,
             doi = {10.1109/ICCOINS.2016.7783239},
            year = {2016},
            note = {cited By 4; Conference of 3rd International Conference on Computer and Information Sciences, ICCOINS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125433},
           pages = {345--350},
           title = {Handwritten digits recognition based on improved label propagation algorith},
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
         journal = {2016 3rd International Conference on Computer and Information Sciences, ICCOINS 2016 - Proceedings},
        keywords = {Entropy; Feature extraction; Information science; Optical character recognition; Pattern recognition; Statistical tests, Algorith; Digit recognition; Entropy-based; Handwritten digits recognition; Label propagation; Practical problems; Recall rate; Semi-supervised, Character recognition},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010303364&doi=10.1109\%2fICCOINS.2016.7783239&partnerID=40&md5=80ce1a6724e3872e461bdb734baab38e},
        abstract = {Handwritten digits recognition is a practical problem in pattern recognition applications, is of academic and commercial interest. It plays an import role in digit recognition and optical character recognition. In this research work, a new method based on label propagation algorithm for handwritten digits recognition is presented. An entropy based feature extraction is hired to evaluate the confidence coefficient for each training digit character. The confidence coefficient will feedback to label propagation algorithm. The label propagation algorithm will retrain again by the guide of feedback from confidence coefficient. According to the experiment results, an overall high recognition rate 98 and recall rate 98 are achieved on the test dataset. It is proved that the proposed handwritten digits recognition algorithm is simple but effective. {\^A}{\copyright} 2016 IEEE.},
          author = {Jie, M. and Aziz, I. A. and Hasbullah, H. and Azizan, S. A. B.},
            isbn = {9781509051342}
}