![]() ![]() Book Editor(s):Muthukumaran Malarvel, Soumya Ranjan Nayak, Surya Narayan Panda, Prasant Kumar Pattnaik, Nittaya Muangnak, īottou L (2010) Large-scale machine learning with stochastic gradient descent. Appl Soft Comput 9(3):990–999Īshok Kumar Sahoo, Pradeepta Kumar Sarangi, Parul Goyal (2020) Indian Sign Language Recognition Using Soft Computing Techniques. IEEE, pp 120–125Īl-Rousan M, Assaleh K, Tala’a A (2009) Video-based signer-independent Arabic sign language recognition using hidden markov models. In: 2016 international conference on information science (ICIS). 2012 4th International Conference on Intelligent Human Computer Interaction (IHCI), pp 1–5Īhmed W, Chanda K, Mitra S (2016) Vision based hand gesture recognition using dynamic time warping for indian sign language. The proposed method achieves the highest training and validation accuracy of 99.76% and 99.64%, respectively, that outperforms other examined systems.Īgrawal SC, Jalal AS, Bhatnagar C (2012) Recognition of indian sign language using feature fusion. To continue the research, a total of 62,400 images of 26 static signs have been taken from various users. Here, we have proposed a fingerspelling recognition system of static signs for the Indian sign language alphabet using convolutional neural networks combined with data augmentation, batch normalization, dropout, stochastic pooling, and diffGrad optimizer. The methodologies to recognize Indian sign language are recently in the developing stage and there is no approach to recognize signs in real-time. The sign language recognition system reduces the communication gaps between normal and deaf-dumb persons. Again, sign language interpreters are not easily available and it is a very costly solution for a long period. As a result, there is a huge communication barrier between normal and deaf-dumb persons. ![]() Yet, normal people do not have any knowledge of such language. ![]() India has the largest deaf population in the world and sign language is the principal medium for such persons to share information with normal people and among themselves. ![]()
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