Method for importing artificial intelligence ultra-deep learning for image recognition

A technology of deep learning and artificial intelligence, applied in the field of information processing, can solve problems affecting the development of artificial intelligence, unclear concepts of artificial intelligence, etc., and achieve the effect of high processing efficiency and clear learning process goals

Pending Publication Date: 2018-05-25
顾泽苍
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AI Technical Summary

Problems solved by technology

[0011] At present, the fundamental reason why ordinary pattern recognition and robot technology are confused with artificial intelligence in society is that the concept of artificial intelligence is not clear. Therefore, all advanced technologies are attributed to artificial intelligence, which will affect the development of artificial intelligence. develop

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  • Method for importing artificial intelligence ultra-deep learning for image recognition
  • Method for importing artificial intelligence ultra-deep learning for image recognition
  • Method for importing artificial intelligence ultra-deep learning for image recognition

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Embodiment Construction

[0086] The embodiments of the present invention will be further described below in conjunction with the accompanying drawings, but the embodiments of the present invention are illustrative rather than limiting.

[0087] figure 1 It is a schematic diagram of the composition of an artificial intelligence ultra-deep learning model.

[0088] First, the following definition of letter expression is performed:

[0089] Set the number of input information and the number of input layer nodes as h (h=1, 2, ..., k), and then set the number of learning times as z = 1, 2, ..., w, and the number of layers of neurons is p (p=1, 2, . . . , e). The image being learned should also be F z (z=1, 2, ..., w), the number of nodes in the hidden layer, that is, the number of nodes in the input layer corresponds to h (h = 1, 2, ..., k), the first learning The micro-machine learning that needs to be learned before the input information is sent to the input layer node is ML z ph , input layer p=1, ...

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Abstract

The invention relates to a method for importing artificial intelligence ultra-deep learning for image recognition in the field of information processing, which is characterized in that an image signalgenerates characteristic information of a characteristic value through micro machine learning, and the characteristic information is inputted into an input layer of an ultra-deep learning neural network; the input layer inputs the characteristic information into a neural layer through micro machine learning; the neural layer generates a neural signal by taking a threshold as a benchmark and inputs the neural signal to a brain layer, and the brain layer performs judgment on a recognition result. The implementation effects are that the computation complexity of ultra-deep learning is O2, the learning process is goal-oriented, the processing efficiency is high, and the method is especially applicable to implementation of a hardware circuit; the method takes the self-organized probability scale as a neuron triggering threshold, thereby being very close to the mechanism of actual cerebral neurons; and the method can be adapted to applications of image recognition objects containing a random component and has a breakthrough on image recognition by applying neural network theories.

Description

【Technical field】 [0001] The invention belongs to the field of information processing, in particular to a method for introducing artificial intelligence ultra-deep learning for image recognition. 【Background technique】 [0002] At present, artificial intelligence has become a hot topic all over the world, and patents related to artificial intelligence are also attracting attention. In this regard, the famous Japanese company Furukawa Electric Co., Ltd. published a patent application for "image processing method and image processing device" (patent document 1) , the patent proposes to select the processing threshold of the image through the artificial intelligence neural network algorithm to extract the outline of the image with high precision. [0003] In the application of automatic driving of automobiles, the famous Japanese Toyota Corporation published the patent of "Driving Direction Estimation Device" (Patent Document 2). In this case, through the machine learning algo...

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Application Information

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IPC IPC(8): G06N3/04G06N3/08
CPCG06N3/08G06N3/043G06N3/047G06N3/045
Inventor 顾泽苍郭南云王悦希
Owner 顾泽苍
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