Mining Vibrational Effects on Off-line Handwriting Recognition
R. Plamondon and S. N. Srihari, “On-Line and Off-Line Handwriting Recognition : A Comprehensive Survey,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 1, pp. 63–84, 2000.
F. Zamora-Martínez, V. Frinken, S. España-Boquera, M. J. CastroBleda, A. Fischer, and H. Bunke, “Neural Network Language Models for Off-line Handwriting Recognition,” Pattern Recognit., vol. 47, no. 4, pp. 1642–1652, 2014.
K. Jayech, M. A. Mahjoub, and N. E. Ben Amara, “Synchronous Multi-Stream Hidden Markov Model for Offline Arabic Handwriting Recognition without Explicit Segmentation,” Neurocomputing, vol. 214, pp. 958–971, 2016.
P. M. Kamble and R. S. Hegadi, “Handwritten Marathi Character Recognition using R-HOG Feature,” Procedia Comput. Sci., vol. 45, no. C, pp. 266–274, 2015.
E. N. Zois, L. Alewijnse, and G. Economou, “Offline Signature Verification and Quality Characterization using Poset-oriented Grid Features,” Pattern Recognit., vol. 54, pp. 162–177, 2016.
S. H. Chang, C. L. Chen, and N. Y. Yu, “Biomechanical Analyses of Prolonged Handwriting in Subjects with and without Perceived Discomfort,” Hum. Mov. Sci., vol. 43, no. 8, pp. 1–8, 2015.
H. M. Hsu, Y. C. Lin, W. J. Lin, C. J. Lin, Y. L. Chao, and L. C. Kuo, “Quantification Of Handwriting Performance: Development of a Force Acquisition Pen for Measuring Hand-grip and Pen Tip Forces,” Meas. J. Int. Meas. Confed., vol. 46, no. 1, pp. 506–513, 2013.
P. H. T. Q. de Almeida, D. M. C. da Cruz, L. A. Magna, and I. S. V. Ferrigno, “An Electromyographic Analysis of Two Handwriting Grasp Patterns,” J. Electromyogr. Kinesiol., vol. 23, no. 4, pp. 838–843, 2013.
A. Choudhary, R. Rishi, and S. Ahlawat, “Off-line Handwritten Character Recognition Using Features Extracted from Binarization Technique,” AASRI Procedia, vol. 4, pp. 306–312, 2013.
K. Assaleh, T. Shanableh, and H. Hajjaj, “Recognition of handwritten Arabic alphabet via hand motion tracking,” J. Franklin Inst., vol. 346, no. 2, pp. 175–189, 2009.
I. Agrawal, A. Vashishtha, and R. Kumar, “Slant Angle Estimation in Handwritten Documents,” Int. J. Comput. Sci. Manag. Stud., vol. 14, no. 5, 2014.
P. Joshi, A. Agarwal, A. Dhavale, R. Suryavanshi, and S. Kodolika, “Handwriting Analysis for Detection of Personality Traits using Machine Learning Approach,” Int. J. Comput. Appl. (0975 – 8887), vol. 130, no. 15, pp. 40–45, 2015.
O. Surinta, M. F. Karaaba, L. R. B. Schomaker, and M. A. Wiering, “Recognition of Handwritten Characters using Local Gradient Feature Descriptors,” Eng. Appl. Artif. Intell., vol. 45, pp. 405–414, 2015.
Á. Morera, Á. Sánchez, J. F. Vélez, and A. B. Moreno, “Gender and Handedness Prediction from Offline Handwriting Using Convolutional Neural Networks,” vol. 2018, 2018.
Y. Chherawala, P. P. Roy, and M. Cheriet, “Combination of Context-dependent Bidirectional Long Short-term Memory Classifiers for Robust Offline Handwriting Recognition,” Pattern Recognit. Lett., vol. 90, pp. 58–64, 2017.
N. Zhi, “Quantitative Assessment of Micrographia and Tremor in Static Handwriting Samples,” 2016.
B. Ribaudo, “The ABC’s of Parkinson’s Disease Handwriting,” 2012. [Online]. Available: https://www.blogger.com/profile/04511379905985881526.
D. Sujitha, “To Analysis of a Hand Writing Recognition using KNearest Neighbour (KNN), Neural Network (NN) and Decision Tree Classifiers,” Int. J. Comput. Sci. Mob. Comput., vol. 4, no. 7, pp. 351–357, 2015.
A. Bal and R. Saha, “An Improved Method for Handwritten Document Analysis Using Segmentation, Baseline Recognition and Writing Pressure Detection,” Procedia Comput. Sci., vol. 93, no. September, pp. 403–415, 2016.
S. Impedovo, “More than Twenty Years of Advancements on Frontiers in Handwriting Recognition,” Pattern Recognit., vol. 47, no. 3, pp. 916–928, 2014.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.