pooling layer
[/ˈpuːlɪŋ ˈleɪər/]
nounpl: pooling layers
camada de agrupamento
1. A layer in a convolutional neural network that reduces the spatial dimensions of feature maps by combining the outputs of neuron clusters at one layer into a single neuron in the next layer
The pooling layer downsamples the input feature maps to reduce computational complexity.
A camada de agrupamento reduz a dimensionalidade das matrizes de características para diminuir a complexidade computacional.
2. A neural network component that performs operations such as max pooling or average pooling to extract dominant features from regions of the input
Max pooling is the most common type of pooling layer used in image recognition models.
O agrupamento máximo é o tipo mais comum de camada de agrupamento usado em modelos de reconhecimento de imagens.
The term 'pooling layer' is a specialized technical term primarily used in artificial intelligence and machine learning contexts. In Brazil, technology professionals and academics may use either the Portuguese translation 'camada de agrupamento' or the English term 'pooling layer' interchangeably, with the English version being more common in international collaborations and when referencing specific frameworks like TensorFlow or PyTorch. This reflects Brazil's growing prominence in AI research and the globalized nature of tech terminology.
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