Human-in-the-Loop Machine Learning to Increase Video Accessibility for Visually Impaired and Blind Users-Reference-Cited by-同舟云学术

Human-in-the-Loop Machine Learning to Increase Video Accessibility for Visually Impaired and Blind Users

Published:2020-07-03 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2020 ACM Designing Interactive Systems Conference
language:
Short-container-title:

Author:

Yuksel Beste F.¹,Fazli Pooyan²,Mathur Umang²,Bisht Vaishali²,Kim Soo Jung¹,Lee Joshua Junhee³,Jin Seung Jung¹,Siu Yue-Ting²,Miele Joshua A.⁴,Yoon Ilmi²

Affiliation:

1. University of San Francisco, San Francisco, CA, USA

2. San Francisco State University, San Francisco, CA, USA

3. University of Washington, Seattle, WA, USA

4. Smith-Kettlewell Eye Research Institute, San Francisco, CA, USA

Funder

Craig Newmark Philanthropies

Center for Computing for Life Sciences, San Francisco State University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3357236.3395433

Reference73 articles.

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2. 3play Media. Accessed Date 2019-09--15. (Accessed Date 2019-09--15). https://www.3playmedia.com/ 3play Media. Accessed Date 2019-09--15. (Accessed Date 2019-09--15). https://www.3playmedia.com/

3. National Aeronautics and Space Administration (NASA). Accessed date 2019-07--17. NASA-TLX. (Accessed date 2019-07--17). https://humansystems.arc.nasa.gov/groups/TLX/tlxapp.php National Aeronautics and Space Administration (NASA). Accessed date 2019-07--17. NASA-TLX. (Accessed date 2019-07--17). https://humansystems.arc.nasa.gov/groups/TLX/tlxapp.php

4. VQA: Visual Question Answering

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