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

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

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...

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書目詳細資料
Main Authors:	Tan, James Chee Min, Cao, Qi, Quek, Chai
其他作者:	School of Computer Science and Engineering
格式:	Article
語言:	English
出版:	2024
主題:	Computer and Information Science Data driven implication Deep neural networks
在線閱讀:	https://hdl.handle.net/10356/178712
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Nanyang Technological University
語言:	English

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