Feature extraction method and system applied to deep learning

A technology of feature extraction and deep learning, applied in the direction of instruments, character and pattern recognition, calculation models, etc., to achieve the effect of reducing the amount of calculation and shortening the calculation time

Active Publication Date: 2018-11-13
CHENGDU IDEALSEE TECH
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Problems solved by technology

[0004] The purpose of the present invention is to provide a feature extraction method and system applied to deep learning, to solve

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  • Feature extraction method and system applied to deep learning
  • Feature extraction method and system applied to deep learning
  • Feature extraction method and system applied to deep learning

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[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0027] All the calculations of the existing deep learning are completed by running programs in the computer, that is, the calculations are all software calculations. On the basis of the deep learning of the prior art, the present invention proposes to pass some calculations in the computer calculations through the scheme of the present invention Convert to optical computing to improve the computing efficiency of deep learning. Embodiments of the present invention w...

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Abstract

The invention discloses a feature extraction method and system applied to deep learning. An existing deep learning calculation mode is improved; in the prior art, for feature extraction in the deep learning, a group of digital signals to be subjected to feature extraction and digital signals of a filter need to be subjected to convolution; the two types of the digital signals are converted into optical signals; at the moment, the optical signals can be simply converted into a frequency domain; the convolution on a time domain is equivalent to the point multiplication on the corresponding frequency domain; the convolution on the time domain is very complex; and the point multiplication operation on the frequency domain can be much simpler. The calculation amount in the deep learning can beeffectively reduced; and after part of the operation is converted into optical calculation, the calculation speed of the part is changed to the optical calculation speed, so that the calculation timeis greatly shortened.

Description

technical field [0001] The present invention relates to the field of artificial intelligence, in particular to a feature extraction method and system applied to deep learning. Background technique [0002] The concept of deep learning originated from the study of artificial neural networks. A multi-layer perceptron with multiple hidden layers is a deep learning structure. Deep learning combines low-level features to form more abstract high-level representation attribute categories or features to discover distributed feature representations of data. Deep learning is a method based on data representation learning in machine learning. In the rapidly developing technological environment, it is increasingly used in machine learning fields such as artificial intelligence, facial recognition, and iris recognition. Human beings are also constantly exploring how to perform feature extraction faster in deep learning. [0003] At present, the convolutional neural network in deep lea...

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Application Information

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IPC IPC(8): G06K9/00G06N99/00
CPCG06F2218/08
Inventor 周旭东宋海涛闫超
Owner CHENGDU IDEALSEE TECH
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