On Interpretability of Artificial Neural Networks: A Survey

• Published in: IEEE transactions on radiation and plasma medical sciences Vol. 5; no. 6; pp. 741 - 760
• Main Authors: Fan, Feng-Lei, Xiong, Jinjun, Li, Mengzhou, Wang, Ge
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Data models; Deep learning; Fuzzy logic; interpretability; Machine learning; Neural networks; survey; Taxonomy; Training; Deep learning; interpretability; survey; neural networks

Deep learning as performed by artificial deep neural networks (DNNs) has achieved great successes recently in many important areas that deal with text, images, videos, graphs, and so on. However, the black-box nature of DNNs has become one of the primary obstacles for their wide adoption in mission-...