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Finding the best way to put media bias research into practice via an annotation app ...
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| 2 |
Audio-driven Character Animation
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In: Doctoral Dissertations (2021)
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| 3 |
Comparison of Machine Learning Models: Gesture Recognition Using a Multimodal Wrist Orthosis for Tetraplegics
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In: The Journal of Purdue Undergraduate Research (2020)
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| 4 |
Practical Natural Language Generation from Knowledge Graphs
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In: Embargoed Honors Theses, University of Nebraska-Lincoln (2019)
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| 5 |
The affordances of process-tracing technologies for supporting L2 writing instruction
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In: English Publications (2018)
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| 6 |
Augmented Reality in Foreign Language Education: A Review of Empirical Studies (增强现实技术在外语教学中的应用：文献综述性研究)
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In: World Languages and Cultures Publications (2018)
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| 7 |
Word Towers: Assessing Domain Knowledge with Non-Traditional Genres
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In: Ashish Amresh (2018)
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| 8 |
Developing a Bilingual, Computer-Tailored, HPV Vaccination Promotion Intervention Targeting Latino Parents
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In: Ashish Amresh (2018)
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| 9 |
Speech Emotion Recognition using Convolutional Neural Networks
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In: Computer Science and Engineering: Theses, Dissertations, and Student Research (2018)
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| 10 |
Potential of Dedicated Language Processing Units in Computer Voice Interaction
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In: Idaho Conference on Undergraduate Research (2017)
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| 11 |
Hand Gesture Recognition for Sign Language Transcription
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In: Boise State University Theses and Dissertations (2017)
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Abstract:
Sign Language is a language which allows mute people to communicate with other mute or non-mute people. The benefits provided by this language, however, disappear when one of the members of a group does not know Sign Language and a conversation starts using that language. In this document, I present a system that takes advantage of Convolutional Neural Networks to recognize hand letter and number gestures from American Sign Language based on depth images captured by the Kinect camera. In addition, as a byproduct of these research efforts, I collected a new dataset of depth images of American Sign Language letters and numbers, and I compared the presented method for image recognition against a similar dataset but for Vietnamese Sign Language. Finally, I present how this work supports my ideas for the future work on a complete system for Sign Language transcription.
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Keyword:
Graphics and Human Computer Interfaces; human computer interaction; image recognition; neural networks; sign language
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URL: https://scholarworks.boisestate.edu/td/1285
https://scholarworks.boisestate.edu/cgi/viewcontent.cgi?article=2322&context=td
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| 12 |
Radical Recognition in Off-Line Handwritten Chinese Characters Using Non-Negative Matrix Factorization
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In: Senior Projects Spring 2016 (2016)
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| 13 |
Paralinguistic Speech Recognition: Classifying Emotion in Speech with Deep Learning Neural Networks
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In: Senior Projects Spring 2016 (2016)
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| 14 |
Developing a Bilingual, Computer-Tailored, HPV Vaccination Promotion Intervention Targeting Latino Parents
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In: Publications (2015)
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| 15 |
Misheard Me Oronyminator: Using Oronyms to Validate The Correctness of Frequency Dictionaries
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In: Master's Theses (2013)
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| 16 |
Two Studies on How a Typeface Congruent With Content Can Enhance Onscreen Communication
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In: Barbara S. Chaparro (2013)
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| 17 |
Is User-Validation Necessary for a Spanish Translation of the Microsoft Product Reaction Cards Tool?
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In: Barbara S. Chaparro (2013)
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| 18 |
An Examination of Presentation Strategies for Textual Data in Augmented Reality
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In: Department of Computer Graphics Technology Degree Theses (2013)
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| 19 |
Cognitive Activity Support Tools: Design of the Visual Interface
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In: Electronic Thesis and Dissertation Repository (2013)
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| 20 |
Detecting Multilingual Lines of Text with Fusion Moves
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In: Electronic Thesis and Dissertation Repository (2013)
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