FE-RNN: a fuzzy embedded recurrent neural network for improving interpretability of underlying neural network

• Main Authors: Tan, James Chee Min, Cao, Qi, Quek, Chai
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Computer and Information Science; Data driven implication; Deep neural networks
• Online Access: https://hdl.handle.net/10356/178712
• Institution: Nanyang Technological University

Deep learning enables effective predictions. But deep structures face some challenges on human interpretability compared to conventional techniques, e.g., fuzzy inference systems. It motivates more research works to alleviate the black box nature of deep structures with performance maintained. This...