conv layer

[kɑnv ˈleɪər]
nounpl: conv layers
camada convolucional
1. A layer in a convolutional neural network that applies convolution operations to input data, using filters to extract features
The first conv layer in the model detects low-level features like edges and textures.
A primeira camada convolucional no modelo detecta características de baixo nível, como bordas e texturas.
2. A computational component in deep learning that uses small matrices (kernels) to scan and process input feature maps
Each conv layer reduces the spatial dimensions while increasing the depth of the feature maps.
Cada camada convolucional reduz as dimensões espaciais enquanto aumenta a profundidade dos mapas de características.
Conv layer is technical jargon primarily used in artificial intelligence, machine learning, and deep learning communities. It is rarely translated or adapted in most professional contexts, with 'conv layer' remaining the standard terminology in Brazil, Portugal, and globally. The abbreviation is preferred in code, documentation, and academic papers to save space and maintain consistency with international conventions.
Synonyms / Sinônimos
convolutional layerconvolution layerfeature extraction layer
Antonyms / Antônimos
fully connected layerdense layer

Regional Variations

General Brazilian
camada convolucional
Standard technical term used in AI and machine learning contexts
Portugal
camada de convolução
Alternative phrasing common in European Portuguese academic texts
International Tech
conv layer
English abbreviation widely used in programming and research documentation across all regions

Related Words

kernelfilterfeature mapstridepaddingpooling layerneural networkCNN
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