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Big data plays an increasingly important role in aircraft integrated health management. This paper introduces the aircraft health management cloud platform, fault feature extraction methods based on deep learning and fault rules network construction, optimization and division.
In this paper, we apply the idea of deep learning to radar waveform recognition. Since the frequency variation with time is the most essential distinction among radar signals with different modulation types, we transform one-dimensional radar signals into time-frequency images (TFIs) using time-frequency analysis and design a convolutional neural network to recognize the frequency variation patterns...
In this paper, we present a deep learning based disease named entity recognition architecture. First, the word-level embedding, character-level embedding and lexicon feature embedding are concatenated as input. Then multiple convolutional layers are stacked over the input to extract useful features automatically. Finally, multiple label strategy, which is firstly introduced, is applied to the output...
The two main problems of biomedical event extraction are trigger identification and argument detection which can both be considered as classification problems. In this paper, we propose a distributed representation method, which combines context, consisted by dependency-based word embedding, and task-based features represented in a distributed way on deep learning models to realize biomedical event...
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