IP Library › Granted Patent US 10,963,739
Granted Patent B2
US 10,963,739 · App. 16/490,939 · Granted Mar 30, 2021

Learning device, learning method, and learning program

Inventor: Shinichiro Yoshida (Tokyo, JP)
Assignee: NEC CORPORATION
G06K9/6256G06K9/628G06K9/6254
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Quick Facts
Patent No.
US 10,963,739
App. No.
16/490,939
Granted
Mar 30, 2021
Kind
B2
Abstract

An intermediate image generating unit 81 generates a plurality of intermediate images from a good product image representing a good product and a faulty product image representing a faulty product. An intermediate image display unit 82 arranges the plurality of intermediate images between the good product image and the faulty product image and displays the same on a display device. A boundary acceptance unit 83 accepts, as a boundary between the good product image and the faulty product image, a designation by a user of a boundary between the intermediate images. A teaching image identification unit 84 identifies the images of the good product image and the faulty product image on the basis of the designated boundary.

Claims (35)

1. A learning device comprising:

at least one memory configured to store instructions; and

at least one processor configured to execute the instructions, to perform:

generating a plurality of intermediate images from a good product image representing a good product and a faulty product image representing a faulty product;

arranging the plurality of intermediate images between the good product image and the faulty product image and displays the same on a display device;

accepting, as a boundary between the good product image and the faulty product image, a designation by a user of a boundary between the intermediate images; and

identifying the images of the good product image and the faulty product image on the basis of the designated boundary.

2. The learning device according to claim 1 , the instructions further comprising:

generating intermediate images in which the degrees of good product images or faulty product images are designated by parameters.

3. The learning device according to claim 1 , the instructions further comprising:

accepting the designation by the user of the position between the displayed intermediate images; and

identifying images on both sides of the designated position as a good product image and a faulty product image.

4. The learning device according to claim 1 , the instructions further comprising:

accepting the designation by the user of an intermediate image parameter; and

identifying the good product image and the faulty product image with the intermediate image generated by the designated parameter as a boundary.

5. The learning device according to claim 1 , the instructions further comprising:

generating a plurality of intermediate images from a good product image, a first faulty product image, and a second faulty product image;

arranging the first faulty product image and the second faulty product image in two axial directions different from each other, with the good product image as a point of origin, and displays the same on the display device;

accepting a designation by the user of a boundary between the good product image and the first faulty product image and of a boundary between the good product image and the second faulty product image; and

identifying the images of the good product image and the faulty product images on the basis of the designated boundaries.

6. The learning device according to claim 1 , the instructions further comprising:

relearning a model by using the good product image and faulty product image identified from the intermediate images.

7. A learning method comprising:

generating a plurality of intermediate images from a good product image representing a good product and a faulty product image representing a faulty product;

arranging the plurality of intermediate images between the good product image and the faulty product image and displaying the same on a display device;

accepting, as a boundary between the good product image and the faulty product image, a designation by a user of a boundary between the intermediate images; and

identifying the images of the good product image and the faulty product image on the basis of the designated boundary.

8. The learning method according to claim 7 , comprising

generating intermediate images in which the degrees of good product images or faulty product images are designated by parameters.

9. A non-transitory computer readable information recording medium configured to store a learning program: when executed by a processor, that performs a method for:

generating a plurality of intermediate images from a good product image representing a good product and a faulty product image representing a faulty product;

an intermediate image display process of arranging the plurality of intermediate images between the good product image and the faulty product image and displaying the same on a display device;

accepting, as a boundary between the good product image and the faulty product image, a designation by a user of a boundary between the intermediate images; and

a teaching image identification process of identifying the images of the good product image and the faulty product image on the basis of the designated boundary.

10. The non-transitory computer readable information recording medium according to claim 9 , further comprising: generating intermediate images in which the degrees of good product images or faulty product images are designated by parameters.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 4, 2019
From: YOSHIDA, SHINICHIRO
To: NEC CORPORATION
Reel/Frame 050257/0918 →
Priority Claims (1)
JP JP2017-057901 · Mar 23, 2017 · national
Continuity (1)
Related Publication 20200019820A1 · Jan 16, 2020
Cited By (1)
US 12,322,084