https://www.ncbi.nlm.nih.gov/pubmed/29975192
Visual Analytics for Explainable Deep Learning.
Abstract
Recently, deep learning has been advancing the state of the art in artificial intelligence to a new level, and humans rely on artificial intelligence techniques more than ever. However, even with such unprecedented advancements, the lack of explanation regarding the decisions made by deep learning models and absence of control over their internal processes act as major drawbacks in critical decision-making processes, such as precision medicine and law enforcement. In response, efforts are being made to make deep learning interpretable and controllable by humans. This article reviews visual analytics, information visualization, and machine learning perspectives relevant to this aim, and discusses potential challenges and future research directions.
- PMID:
- 29975192
- DOI:
- 10.1109/MCG.2018.042731661
딥러닝을 어떻게 시각화 해서 보여주고 납득시킬 것이냐는
지속되는 이슈~
2018 IEEE comp Graph Appl - Visual Analytics for Explainable Deep Learning.pdf
