Title:
NEURAL NETWORK-TYPE IMAGE PROCESSING DEVICE
Document Type and Number:
WIPO Patent Application WO/2019/176479
Kind Code:
A1
Abstract:
This neural network-type image processing device is provided with an input layer which comprises one unit where an input image is inputted, an output layer which comprises one unit where an output image is outputted, and multiple intermediate layers which are arranged between the input layer and the output layer and each of which comprises multiple units, wherein the unit of the input layer, the units of the intermediate layers, and the unit of the output layer are fully connected with connection coefficients. The units of the intermediate layers are image processing modules which perform image processing on the image inputted to said units. The input image is inputted from the unit of the input layer, passes through the units of the intermediate layers, and is then outputted as an output image from the unit of the output layer; the connection coefficients are updated with learning based on a backpropagation algorithm.
More Like This:
Inventors:
IJIRI YOSHIHISA (JP)
Application Number:
PCT/JP2019/006184
Publication Date:
September 19, 2019
Filing Date:
February 20, 2019
Export Citation:
Assignee:
OMRON TATEISI ELECTRONICS CO (JP)
International Classes:
G06T7/00
Foreign References:
| JP2017097585A | 2017-06-01 | |||
| US20160209995A1 | 2016-07-21 | |||
| JP2004362440A | 2004-12-24 | |||
| JPH0630253A | 1994-02-04 |
Other References:
KADOKAWA ET AL.: "Well-understood artificial intelligence", ARTIFICIAL INTELLIGENCE, vol. 3, no. 3rd edition, 25 January 2017 (2017-01-25), pages 144 - 153
SIMO-SERRA, EDGAR ET AL.: "Learning To Simplify: Fully Convolutional Networks for Rough Sketch Cleanup", ACM TRANSACTIONS ON GRAPHICS, vol. 35, no. 4, July 2016 (2016-07-01), XP058275857
SIMO-SERRA, EDGAR ET AL.: "Learning To Simplify: Fully Convolutional Networks for Rough Sketch Cleanup", ACM TRANSACTIONS ON GRAPHICS, vol. 35, no. 4, July 2016 (2016-07-01), XP058275857
Attorney, Agent or Firm:
TACHIBANA, Kenji et al. (JP)
Download PDF: