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Deep Learning for Understanding the Human

Published: 20 April 2018 Publication History

Abstract

We will explore how deep learning approaches can be used for perceiving and interpreting the state and behavior of human beings in images, video, audio, and text data. The course will cover how convolutional, recurrent and generative neural networks can be used for applications of face recognition, eye tracking, cognitive load estimation, emotion recognition, natural language processing, voice-based interaction, and activity recognition. The course is open to beginners and is designed for those who are new to deep learning, but it can also benefit advanced researchers in the field looking for a practical overview of deep learning methods and their application.

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Published In

cover image ACM Conferences
CHI EA '18: Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
April 2018
3155 pages
ISBN:9781450356213
DOI:10.1145/3170427
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 April 2018

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Author Tags

  1. computer vision
  2. deep learning
  3. human-centered artificial intelligence
  4. natural language processing

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  • Course

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CHI '18
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Acceptance Rates

CHI EA '18 Paper Acceptance Rate 1,208 of 3,955 submissions, 31%;
Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

Upcoming Conference

CHI 2025
ACM CHI Conference on Human Factors in Computing Systems
April 26 - May 1, 2025
Yokohama , Japan

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