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شبکه عصبی بازگشتی دوطرفه (Bidirectional RNN)×شبکه عصبی کانولوشنی گشادشده (Dilated CNN)×
حوزهیادگیری عمیقیادگیری عمیق
خانوادهMachine learningMachine learning
سال پیدایش19972016
پدیدآورSchuster, M. & Paliwal, K.K.van den Oord, A. et al.; Bai, S., Kolter, J.Z. & Koltun, V.
نوعRecurrent neural network (sequence model)Deep learning (dilated 1D convolutional network)
منبع بنیادینSchuster, 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 ↗
نام‌های دیگرÇift Yönlü RNN / BiLSTM / BiGRU, bidirectional recurrent neural network, BiLSTM, BiGRUDilate Edilmiş CNN (WaveNet / TCN), WaveNet, Temporal Convolutional Network, TCN
مرتبط55
خلاصهA 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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ScholarGateمقایسهٔ روش‌ها: Bidirectional RNN · Dilated CNN. بازیابی‌شده در 2026-06-19 از https://scholargate.app/fa/compare