Topic
Devanagari
About: Devanagari is a research topic. Over the lifetime, 655 publications have been published within this topic receiving 7428 citations. The topic is also known as: Deva nagari & Hindi Script.
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01 Jan 2012
1 citations
TL;DR: An finger point based signed language symbol to text identification and classification algorithm that is based upon RGB image datasets that provides an excellent classification rate which promises upliftment for research in the upcoming future is presented.
Abstract: In this paper, we present an finger point based signed language symbol to text identification and classification algorithm that is based upon RGB image datasets. The palm sized images based upon different sizes, backgrounds, orientation are captured to be preprocessed as per the requirements of developing a convolution neural network based algorithm. This algorithm utilizes Alexnet for the preprocessing requisites where in 47 symbols of Devanagari script are augmented based on the reference rulebook created for our requirements as highlighted in the paper. At the primary level this algorithm provides an excellent classification rate which promises upliftment for our research in the upcoming future. We have provided detailed steps and discussion on the classification parameters considered for our algorithm which is implemented on MATLAB platform with the help of machine learning solution libraries.
1 citations
TL;DR: In this paper , the authors presented handwritten isolated characters of the Devanagari script, which contains ten numerals, 13 vowels, and 33 consonants, and collected samples are digitized and pre-processed.
1 citations
01 Jan 2019
TL;DR: In this article, a deep learning-based model was proposed to recognize Devanagari script characters in real time by analyzing hand movements, which can be used for character recognition.
Abstract: The revolutionization of the technology behind optical character recognition (OCR) has helped it to become one of those technologies that have found plenty of uses in the entire industrial space. Today, the OCR is available for several languages and have the capability to recognize the characters in real time, but there are some languages for which this technology has not developed much. All these advancements have been possible because of the introduction of concepts like artificial intelligence and deep learning. Deep Neural Networks have proven to be the best choice when it comes to a task involving recognition. There are many algorithms and models that can be used for this purpose. This project tries to implement and optimize a deep learning-based model which will be able to recognize Devanagari script’s characters in real time by analyzing the hand movements.
1 citations