| dbo:abstract |
A layer in a deep learning model is a structure or network topology in the model's architecture, which takes information from the previous layers and then passes it to the next layer. There are several famous layers in deep learning, namely convolutional layer and maximum pooling layer in the convolutional neural network. Fully connected layer and ReLU layer in vanilla neural network. RNN layer in the RNN model and deconvolutional layer in autoencoder etc. (en) 층(層) 또는 레이어(layer)란 인공 신경망에서 데이터를 모아서 보내는 단계와 관련된 개념이다. 순방향 신경망에서는 먼저 나온 층에서 뒤에 나오는 층으로만 신호를 전달할 수 있고, 순환 신경망에서는 그렇지 않다. (ko) 层，或层次，是深度学习模型模型架构中的一种结构或網路拓撲，它从上一层获取信息，然后将信息传递给下一层。深度学习中有几个著名的层，即卷积神经网络中的卷积层和最大。基本神经网络中的全连接层和ReLU层。循環神經網路中的RNN层和自动编码器中的等。 (zh) |
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owl:Thing |
| rdfs:comment |
A layer in a deep learning model is a structure or network topology in the model's architecture, which takes information from the previous layers and then passes it to the next layer. There are several famous layers in deep learning, namely convolutional layer and maximum pooling layer in the convolutional neural network. Fully connected layer and ReLU layer in vanilla neural network. RNN layer in the RNN model and deconvolutional layer in autoencoder etc. (en) 층(層) 또는 레이어(layer)란 인공 신경망에서 데이터를 모아서 보내는 단계와 관련된 개념이다. 순방향 신경망에서는 먼저 나온 층에서 뒤에 나오는 층으로만 신호를 전달할 수 있고, 순환 신경망에서는 그렇지 않다. (ko) 层，或层次，是深度学习模型模型架构中的一种结构或網路拓撲，它从上一层获取信息，然后将信息传递给下一层。深度学习中有几个著名的层，即卷积神经网络中的卷积层和最大。基本神经网络中的全连接层和ReLU层。循環神經網路中的RNN层和自动编码器中的等。 (zh) |
| rdfs:label |
Layer (deep learning) (en) 층 (기계 학습) (ko) 層 (深度學習) (zh) |
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dbr:Convolutional_neural_network |
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wikidata:Layer (deep learning) dbpedia-ko:Layer (deep learning) dbpedia-zh:Layer (deep learning) https://global.dbpedia.org/id/FnXvQ |
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