论文标题
基于Bilstm-CNN的多任务学习方法用于纤维故障诊断
A BiLSTM-CNN based Multitask Learning Approach for Fiber Fault Diagnosis
论文作者
论文摘要
提出了一种基于堆叠的双向长期记忆（BILSTM）网络和卷积神经网络（CNN）的新型多任务学习方法，用于检测，定位，表征和识别纤维故障。它的表现胜过常规使用的技术。
A novel multitask learning approach based on stacked bidirectional long short-term memory (BiLSTM) networks and convolutional neural networks (CNN) for detecting, locating, characterizing, and identifying fiber faults is proposed. It outperforms conventionally employed techniques.
