Explainable Facial Expression Recognition for People with Intellectual Disabilities
arxiv(2024)
摘要
Facial expression recognition plays an important role in human behaviour,
communication, and interaction. Recent neural networks have demonstrated to
perform well at its automatic recognition, with different explainability
techniques available to make them more transparent. In this work, we propose a
facial expression recognition study for people with intellectual disabilities
that would be integrated into a social robot. We train two well-known neural
networks with five databases of facial expressions and test them with two
databases containing people with and without intellectual disabilities.
Finally, we study in which regions the models focus to perceive a particular
expression using two different explainability techniques: LIME and RISE,
assessing the differences when used on images containing disabled and
non-disabled people.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要