convolutional network

[kən-ˈvō-lə-ˈshnəl ˈnet-ˌwərk]
nounpl: convolutional networks
rede neural convolucionada
1. A deep learning architecture composed of layers that apply convolution operations to input data, particularly effective for processing grid-like data such as images
The convolutional network successfully identified cats and dogs in the image dataset with 99% accuracy.
A rede neural convolucionada identificou com sucesso gatos e cães no conjunto de dados de imagens com 99% de precisão.
2. A neural network model that uses convolutional layers to automatically learn spatial hierarchies of features from raw input
Modern computer vision applications rely heavily on convolutional networks for object detection and image classification.
As aplicações modernas de visão computacional dependem muito de redes neurais convolucionadas para detecção de objetos e classificação de imagens.
Convolutional networks are fundamental to modern artificial intelligence and are commonly referred to by the acronym CNN in both English and Portuguese-speaking tech communities. In Brazil, while the full Portuguese translation 'rede neural convolucionada' is used in academic writing, tech professionals frequently use the English acronym CNN or the abbreviated English term 'ConvNet' in casual conversation and documentation.
Synonyms / Sinônimos
CNNConvNetconvolutional neural networkdeep convolutional network

Regional Variations

General Brazilian
rede neural convolucionada
Most common translation in Brazil
São Paulo
rede neural convolucionada / CNN
Tech professionals often use English term or abbreviation
Rio de Janeiro
rede neural convolucionada
Standard usage in academic and research contexts
Portugal
rede neural convolucional
European Portuguese variant; slightly different adjective form

Related Words

neural networkdeep learningconvolutionfeature extractionpooling layerfully connected layerimage recognitioncomputer vision

Related Idioms & Phrases

training a convolutional network
tuning convolutional network parameters
stacking convolutional layers
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