Examples of using Convolutional in English and their translations into Portuguese
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MTCNN(multi-task cascaded convolutional neural networks)
by using deep learning Convolutional Neural Networks
called convolutional deep belief network(cdbn),
Learn about a new method for convolutional layers for x86 architectures(such as Intel® Xeon PhiTM
The methodology is based on a convolutional forward operator modeling and the sampling of high resolution model parameters of the subsurface,
which is truncated by cpml technique convolutional perfectly matched layers.
reduce the cost of finite difference method, a convolutional differentiator operator, in which we used different functions window to generate new coefficients of finite differences.
more relatively simple convolutional codes plus interleaving that creates a more uniform distribution of errors.
we will be building a baseline convolutional neural network(CNN)
the afdtd computational domain is truncated by the cpml technique convolutional perfectly matched layer.
The objective of this work was to compare convolutional neural network, a deep learning method,
A convolutional encoder is a discrete linear time-invariant system.
We use as feature extractors convolutional networks with random weights, which are applied
This paper studies the impact of the payload size in the energy efficiency in a point-to-point link in a wireless sensor network using convolutional codes.
Convolutional neural networks brought to the computer vision
By choosing pairs of convolutional encoders, with the bit error probability(ber) of pe 10-4,
using artificial descriptors, convolutional neural networks(cnn) and cnn as a natural descriptor where the descriptors are obtained from a large pre-trained cnn in a different dataset.
the outage probability and the frame error rate(using convolutional codes), showing that,
tune, and deploy convolutional neural networks(CNNs) on low-power applications that require real-time inferencing.
Convolutional codes, by contrast, continuously add redundant bits