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Easy Visual Question Answering With Video
In this project, we expand on the easy-VQA dataset to create a new dataset of simple, short-length videos and corresponding questions and answers about them. We then implement two models to perform the VQA task. The first model answers questions about videos that contain a single shape and the second model performs VQA on videos that contain two shapes using attention. Github Repository |
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Easy Visual Question Answering For Counting
This project is motivated by the tendency for visual question answering (VQA) models to struggle with counting questions. Another goal is to provide a small, simple dataset for quick experimentation. Our code is based on easy-VQA-keras, but adapted for counting. We hope this code will provide a starting point to investigate more challenging counting problems. Github Repository |
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Code-A-Story
This online tool to help integrate computer science and literacy education for elementary school students was designed as part of the NAF grant: "CS for Appalachia: A research-practice partnership for integrating computer science into East Tennessee schools" (NSF Grant No. 1923509). Project website (login needed) |