DEEP LEARNING-BASED SELF-ADAPTIVE LEARNING ENGINE MODULE

Title:

DEEP LEARNING-BASED SELF-ADAPTIVE LEARNING ENGINE MODULE

Document Type and Number:

WIPO Patent Application WO/2018/131749

Kind Code:

A1

Abstract:

According to the deep learning-based self-adaptive learning engine module suggested by the present invention, the mechanism of the human brain for identifying a mission on its own by understanding a situation, and resolving the situation by creating a model can be effectively implemented by self-organizing a DNA mission and self-configuring an artificial neural network DNA model by combining self-adaptive technology and deep learning-based learning technology. Further, the present invention is implemented in the form of a module and can therefore be easily applied to various systems and, by performing self-adaptive learning by using structured data and unstructured data, can be applied for various purposes, such as understanding a situation, scheduling, decision making, prediction, recommendation, and taking a measure according to a situation, by making use of the learning result.

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Inventors:

YOON HEE BYUNG (KR)

Application Number:

PCT/KR2017/002341

Publication Date:

July 19, 2018

Filing Date:

March 03, 2017

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Assignee:

THE DNA SYSTEM (KR)

International Classes:

G06N3/12; G06N3/08

Foreign References:

KR20060076839A	2006-07-05
KR101607209B1	2016-03-30
JP2003317073A	2003-11-07
KR20070043126A	2007-04-25
JP2005182449A	2005-07-07

Attorney, Agent or Firm:

KIM, Keon Woo (KR)

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