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A BiLSTM-CNN based Multitask Learning Approach for Fiber Fault Diagnosis

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Abstract

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.

© 2021 The Author(s)

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