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

• المؤلفون الرئيسيون: Tan, James Chee Min, Cao, Qi, Quek, Chai
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2024
• الموضوعات: Computer and Information Science; Data driven implication; Deep neural networks
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/178712

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...