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Gesture recognition is an area of research and development in computer science and language technology concerned with the recognition and interpretation of human gestures. A subdiscipline of computer vision , [ citation needed ] it employs mathematical algorithms to interpret gestures.
Sketch recognition describes the process by which a computer, or artificial intelligence can interpret hand-drawn sketches created by a human being, or other machine. [1] Sketch recognition is a key frontier in the field of artificial intelligence and human-computer interaction , similar to natural language processing or conversational ...
In a 2008, an episode of the television series The Simpsons, Lisa Simpson travels to the underwater headquarters of Mapple to visit Steve Mobbs, who is shown to be performing multiple multi-touch hand gestures on a large touch wall. In the 2009, the film District 9 the interface used to control the alien ship features similar technology. [60]
Gesture Search was based on the early research work [3] and primarily developed by Yang Li, a Research Scientist at Google. At the time of its launch, the application was made available only to the elite devices such as the Google Nexus One & the Motorola Milestone and was regarded as an extension to Google's handwriting recognition programme, [4] prominently available only in the US. [5]
Intelligent character recognition (ICR) makes use of continuously improving algorithms to collect more information about the variances in hand-printed characters and more precisely identify them. ICR, which was created in the early 1990s to aid in the automation of forms processing, enables the conversion of manually entered data into text that ...
Application Adobe Acrobat starts including support for OCR on any PDF file. [7] 2011 Application Word-frequency lookup Google Ngram Viewer is developed to chart frequencies of words on any source printed from 1950 to 2008. [25] [26] 2013 Application The MNIST database is created to train machine learning models in pattern recognition. [27] 2015 ...
A 2016 analysis of the accuracy and reliability of the OCR packages Google Docs OCR, Tesseract, ABBYY FineReader, and Transym, employing a dataset including 1227 images from 15 different categories concluded Google Docs OCR and ABBYY to be performing better than others. [22]
The data obtained by this form is regarded as a static representation of handwriting. Offline handwriting recognition is comparatively difficult, as different people have different handwriting styles. And, as of today, OCR engines are primarily focused on machine printed text and ICR for hand "printed" (written in capital letters) text.