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شبکه عصبی کانولوشنی گشادشده (Dilated CNN)×شبکه عصبی بازگشتی دوطرفه (Bidirectional RNN)×
حوزهیادگیری عمیقیادگیری عمیق
خانوادهMachine learningMachine learning
سال پیدایش20161997
پدیدآورvan den Oord, A. et al.; Bai, S., Kolter, J.Z. & Koltun, V.Schuster, M. & Paliwal, K.K.
نوعDeep learning (dilated 1D convolutional network)Recurrent neural network (sequence model)
منبع بنیادینvan den Oord, A. et al. (2016). WaveNet: A Generative Model for Raw Audio. arXiv. link ↗Schuster, M. & Paliwal, K.K. (1997). Bidirectional Recurrent Neural Networks. IEEE Transactions on Signal Processing, 45(11), 2673–2681. DOI ↗
نام‌های دیگرDilate Edilmiş CNN (WaveNet / TCN), WaveNet, Temporal Convolutional Network, TCNÇift Yönlü RNN / BiLSTM / BiGRU, bidirectional recurrent neural network, BiLSTM, BiGRU
مرتبط55
خلاصهA 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.A 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.
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ScholarGateمقایسهٔ روش‌ها: Dilated CNN · Bidirectional RNN. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare