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Using multiple sensors for mobile sign language recognition
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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The functions of formulaic language: an integrated model
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Real-time American sign language recognition using desk and wearable computer based video
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A tutorial on hidden Markov models and selected applications in speech recognition
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Recursive identification of gesture inputs using hidden Markov models
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Invariant features for 3-D gesture recognition
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Recognizing human action in time-sequential images using hidden Markov model
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Adapting hidden Markov models for ASL recognition by using three-dimensional computer vision methods
inferredcites →https://doi.org/10.1109/robot.1996.509165openalex-snapshot
Online, interactive learning of gestures for human/robot interfaces
inferredcites →https://doi.org/10.1145/108844.108900openalex-snapshot
Gesture recognition using recurrent neural networks
inferredcites →https://doi.org/10.1145/122488.122499openalex-snapshot
Hand gesture coding based on experiments using a hand gesture interface device
inferredcites →https://doi.org/10.21437/icslp.2002-377openalex-snapshot
Speech and language processing for a constrained speech translation system
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Hand Gesture Recognition System Based on a Geometric Model and Rule Based Classifier
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Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.