convolutional layer
[/ˌkɑːnvəˈluːʃənəl ˈleɪər/]
nounpl: convolutional layers
camada convolucional
1. A fundamental building block in convolutional neural networks (CNNs) that applies convolution operations to input data using learnable filters or kernels to extract features
The first convolutional layer in the neural network detects low-level features such as edges and textures.
A primeira camada convolucional da rede neural detecta características de baixo nível, como bordas e texturas.
2. A layer that performs element-wise multiplication and summation between a filter and portions of the input, moving the filter across the input space
Each convolutional layer learns to recognize different patterns as it processes image data through the network.
Cada camada convolucional aprende a reconhecer diferentes padrões conforme processa dados de imagem pela rede.
This is technical terminology specific to machine learning and artificial intelligence fields. It is used identically in both Brazilian Portuguese and European Portuguese scientific literature. The term has become standardized across international AI research communities and is rarely translated or adapted colloquially. In Brazil, with the growth of tech startups and AI research centers in São Paulo and Rio de Janeiro, this term is increasingly used by software engineers, data scientists, and researchers.
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