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شبكة عصبية متكررة ثنائية الاتجاه×شبكة الالتفاف المتمددة (Dilated CNN)×
المجالالتعلم العميقالتعلم العميق
العائلةMachine learningMachine learning
سنة النشأة19972016
صاحب الطريقةSchuster, M. & Paliwal, K.K.van den Oord, A. et al.; Bai, S., Kolter, J.Z. & Koltun, V.
النوعRecurrent neural network (sequence model)Deep learning (dilated 1D convolutional network)
المصدر التأسيسيSchuster, M. & Paliwal, K.K. (1997). Bidirectional Recurrent Neural Networks. IEEE Transactions on Signal Processing, 45(11), 2673–2681. DOI ↗van den Oord, A. et al. (2016). WaveNet: A Generative Model for Raw Audio. arXiv. link ↗
الأسماء البديلةÇift Yönlü RNN / BiLSTM / BiGRU, bidirectional recurrent neural network, BiLSTM, BiGRUDilate Edilmiş CNN (WaveNet / TCN), WaveNet, Temporal Convolutional Network, TCN
ذات صلة55
الملخصA Bidirectional RNN, introduced by Schuster and Paliwal in 1997, processes a sequence in both forward and backward directions so that every position has access to its full surrounding context. With LSTM or GRU cells (BiLSTM/BiGRU) it is the standard approach for named-entity recognition, sequence labelling, and speech recognition.A Dilated CNN is a one-dimensional convolutional network whose receptive field grows exponentially with depth, letting it model long-range structure in time series and audio signals. WaveNet (van den Oord et al., 2016) and the Temporal Convolutional Network of Bai, Kolter and Koltun (2018) are the prominent members of this family.
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ScholarGateقارن الطرق: Bidirectional RNN · Dilated CNN. استُرجع بتاريخ 2026-06-19 من https://scholargate.app/ar/compare