多模态机器学习教程

Louis-Philippe Morency, P. Liang, Amir Zadeh
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引用次数: 11

摘要

多模态机器学习涉及对来自多个异构数据源的信息进行集成和建模。这是一个具有挑战性但又至关重要的领域,在多媒体、情感计算、机器人、金融、HCI和医疗保健等领域有许多实际应用。本教程基于一篇关于多模态机器学习的调查论文的新版本,以及之前给出的教程和学术课程,将描述一个关于多模态机器学习的最新分类,综合其核心技术挑战和未来研究的主要方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tutorial on Multimodal Machine Learning
Multimodal machine learning involves integrating and modeling information from multiple heterogeneous sources of data. It is a challenging yet crucial area with numerous real-world applications in multimedia, affective computing, robotics, finance, HCI, and healthcare. This tutorial, building upon a new edition of a survey paper on multimodal ML as well as previously-given tutorials and academic courses, will describe an updated taxonomy on multimodal machine learning synthesizing its core technical challenges and major directions for future research.
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