Examples of using Convolutional in English and their translations into Italian
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Object detection: the object detection system is based on a deep convolutional neural network.
In image processing In digital image processing convolutional filtering plays an important role in many important algorithms in edge detection and related processes.
The fact that errors appear as"bursts" should be accounted for when designing a concatenated code with an inner convolutional code.
You can use convolutional neural networks(ConvNets, CNNs) and long short-term memory(LSTM)
The second sub-block is n/2 parity bits for the payload data, computed using a recursive systematic convolutional code RSC code.
which is extensively used for convolutional neural networks.
Image classification takes advantage of convolutional neural networks and distinguishes between documents that are visually different.
The resulting recurrent convolutional network allows for the flexible incorporation of contextual information to iteratively resolve local ambiguities.
The popular solution for this problem is to interleave data before convolutional encoding, so that the outer block(usually Reed-Solomon)
LeNet-5, a pioneering 7-level convolutional network by LeCun et al. in 1998,
In addition to the invention of Turbo Codes, Claude Berrou also invented recursive systematic convolutional(RSC) codes, which are used in the example implementation of turbo codes described in the patent.
Internal encoder: A second level of error correction is given by a punctured convolutional code, which is often denoted in STBs menus as FEC Forward error correction.
by using deep learning Convolutional Neural Networks
domain specific languages and Machine Learning frameworks, in particular the ones oriented to convolutional neural networks.
More specifically, we will use the recently introduced intrinsic convolutional neural networks on 3D scans of human faces to automatically learn the mapping from facial geometry to genetics features, which will then be reversed to reconstruct the face from DNA.
including serial versions serial concatenated convolutional codes and repeat-accumulate codes.
including Reed-Solomon corrected convolutional codes, although these systems are too complex for practical implementations of iterative decoders.
Simple Viterbi-decoded convolutional codes are now giving way to turbo codes, a new class of iterated short convolutional codes that closely approach the theoretical limits imposed by Shannon's theorem with much less decoding complexity than the Viterbi algorithm on the long convolutional codes that would be required for the same performance.
Objective: Build convolutional networks from scratch.
Convolutional codes were introduced in 1955 by Peter Elias.