1. N Pashaloudi,K Margaritis (1112). Hidden markov model for sign language recognition: A review. Proc. 2nd Hellenic Conf. AI, SETN-2002, 343354.
2. L Dipietro,A Sabatini,P Dario (2008). A survey of glove-based systems and their applications. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 38(4), 461-482.
3. M Moni (2009). Hmm based hand gesture recognition: A review on techniques and approaches. ICCSIT 2009. 2nd IEEE International Conference on, 433-437.
4. S Kausar,M Javed (2011). A survey on sign language recognition. Frontiers of Information Technology (FIT), 95-98.
5. H Riad,S Elmonier,A Shohieb,Asem (2012). SignsWorld: Deeping into the Silence World and Hearing Its Signs (State of the Art). International Journal of Computer Science and Information Technology, 4(1), 189-208.
6. P Vijay,N Suhas,C Chandrashekhar,D Dhananjay (2012). Recent developments in sign language recognition: a review. Int J Adv Comput Eng Commun Technol, 1, 21-26.
7. M Mohandes,M Deriche,J Liu (2014). Image-Based and Sensor-Based Approaches to Arabic Sign Language Recognition. IEEE Transactions on Human-Machine Systems, 44(4), 551-557.
8. N Salleh,J Jais,L Mazalan,R Ismail,S Yussof,A Ahmad,A Anuar,D Mohamad (2006). Sign language to voice recognition: hand detection techniques for vision-based approach. Current Developments in Technology-Assisted Education, 422
9. R Naoum,H Owaied,S Joudeh (2012). Development of a new Arabic sign language recognition using k-nearest neighbor algorithm. Journal of Emerging Trends in Computing and Information Sciences, 3(8)
10. Mohamed Mohandes (2013). Recognition of Two-Handed Arabic Signs Using the CyberGlove. Arabian Journal for Science and Engineering, 38(3), 669-677.
11. Ahmed Samirelons,Magdy Abull‐ela,Mohamed Tolba (2013). Pulse‐coupled neural network feature generation model for Arabic sign language recognition. IET Image Processing, 7(9), 829-836.
12. M Mohandes,M Deriche (2013). Arabic sign language recognition by decisions fusion using Dempster-Shafer theory of evidence. 2013 Computing, Communications and IT Applications Conference (ComComAp), 90-94.
13. Khaled Assaleh,Tamer Shanableh,Mohammed Zourob (2012). Low Complexity Classification System for Glove-Based Arabic Sign Language Recognition. Lecture Notes in Computer Science, 262-268.
14. H Khaled,S Sayed,E Saad,H Ali (2015). Hand gesture recognition using modified 1$ and background subtraction algorithms. Mathematical Problems in Engineering, 2015
15. A Galvis,B Batoczki,I Pecson,T Sellers,E Goroza,C Nakamura (2001). A domestic case of pediatric miliary tuberculosis. Archives of Microbiology and Infectious Diseases, 1(1), 753-759.
16. Omar Al-Jarrah,Alaa Halawani (2001). Recognition of gestures in Arabic sign language using neuro-fuzzy systems. Artificial Intelligence, 133(1-2), 117-138.
17. M Al-Rousan,M Hussain (2001). Automatic recognition of arabic sign language finger spelling. International Journal of Computers and Their Applications, 8, 80-88.
18. O Al-Jarrah,F Al-Omari (2007). Improving gesture recognition in the arabic sign language using texture analysis. Applied Artificial Intelligence, 21(1), 11-33.
19. M Maraqa,R Abu-Zaiter (2008). Recognition of arabic sign language (arsl) using recurrent neural networks. Applications of Digital Information and Web Technologies, 478-481.
20. M Maraqa,F Al-Zboun,M Dhyabat,R Zitar (2012). Recognition of Arabic sign language (arsl) using recurrent neural networks. Recognition of Arabic sign language (arsl) using recurrent neural networks
21. E Hemayed,A Hassanien (2010). Edge-based recognizer for Arabic sign language alphabet (ars2v-arabic sign to voice). Computer Engineering Conference (ICENCO), 121-127.
22. S Elons,M Abull-Ela,M Tolba (2013). Neutralizing lighting nonhomogeneity and background size in pcnn image signature for Arabic sign language recognition. Neural Computing and Applications, 22(1), 47-53.
23. M Samirelons,M Abull-Ela,Tolba (2013). Pulsecoupled neural network feature generation model for arabic sign language recognition. IET Image Processing, 7(9), 829-836.
24. Z Mahmoud,M Alaa,A -R,M Sameh,Elsayed (2015). Arabic alphabet and numbers sign language recognition. International Journal of Advanced Computer Science and Applications (ijacsa), 6(3)
25. M Mohandes,S Aliyu,M Deriche (2014). Arabic sign language recognition using the leap motion controller. IEEE 23rd International Symposium on, 960-965.
26. D Olshausen,Field (2004). Sparse coding of sensory inputs. Current opinion in neurobiology, 14(4), 481-487.
27. J Field (1994). What is the goal of sensory coding?. Neural computation, 6(4), 559-601.
28. Marc'aurelio Ranzato,Fu Huang,Y.-L Boureau,Yann Lecun (2007). Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition. 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8.
29. J Yang,K Yu,Y Gong,T Huang (2009). Linear spatial pyramid matching using sparse coding for image classification. Computer Vision and Pattern Recognition, 1794-1801.
30. John Wright,Yi Ma,Julien Mairal,Guillermo Sapiro,Thomas Huang,Shuicheng Yan (2010). Sparse Representation for Computer Vision and Pattern Recognition. Proceedings of the IEEE, 98(6), 1031-1044.
31. Y.-L Boureau,F Bach,Y Lecun,J Ponce (2010). Learning mid-level features for recognition. Computer Vision and Pattern Recognition (CVPR), 2559-2566.
32. E Hasasneh,P Frenoux,Tarroux (2012). Semantic Place Recognition based on Deep Belief Networks and Tiny Images. Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics, 236-241.
33. K Labusch,T Martinetz (2010). Learning sparse codes for image reconstruction. ESANN
34. Geoffrey Hinton,Simon Osindero,Yee-Whye Teh (2006). A Fast Learning Algorithm for Deep Belief Nets. Neural Computation, 18(7), 1527-1554.
35. P Smolensky (1987). Information processing in dynamical systems: Foundations of harmony theory. Parallel Distributed Processing, 1, 194-281.
36. G Hinton (2002). Training products of experts by minimizing contrastive divergence. Neural computation, 14(8), 1771-1800.
37. (2007). The arabic dictionary of gestures for the deaf. The arabic dictionary of gestures for the deaf
38. G Krizhevsky,Hinton (2010). Factored 3-way restricted Boltzmann machines for modeling natural images. International Conference on Artificial Intelligence and Statistics, 621-628.
39. Honglak Lee,Roger Grosse,Rajesh Ranganath,Andrew Ng (2009). Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. Proceedings of the 26th Annual International Conference on Machine Learning, 609-616.
40. Mohammad Norouzi,Mani Ranjbar,Greg Mori (2009). Stacks of convolutional Restricted Boltzmann Machines for shift-invariant feature learning. 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2735-2742.
41. F Attneave (1954). Some informational aspects of visual perception. Psychological review, 61(3), 183.
42. H Barlow (2001). Redundancy reduction revisited. Network: Computation in Neural Systems, 12(3), 241-253.
43. A Coates,H Ng,Lee (2011). An analysis of singlelayer networks in unsupervised feature learning. International conference on artificial intelligence and statistics, 215-223.
44. Geoffrey Hinton,Alex Krizhevsky,Sida Wang (2011). Transforming Auto-Encoders. Lecture Notes in Computer Science, 44-51.
45. Geoffrey Hinton (2009). Deep belief networks. Scholarpedia, 4(5), 5947.
46. Krizhevsky (2009). Learning multiple layers of features from tiny images. Tech. Rep
47. G Hinton (2010). A practical guide to training restricted boltzmann machines. Momentum, 9(1), 926.
48. Antonio Torralba,Rob Fergus,Yair Weiss (2008). Small codes and large image databases for recognition. 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8.