Paper Abstract and Keywords |
Presentation |
2021-02-18 14:50
A Note on Estimation of Deteriorated Regions Based on Anomaly Detection from Rubber Material Electron Microscope Images
-- Verification of Feature Representations Extracted from Deep Learning Models -- Masanao Matsumoto, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ) |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
This paper presents an anomaly detection method for estimation of deteriorated regions from rubber material electron microscope images. In order to develop rubber materials with high durability, it is important to clarify the cause of deterioration. For analyzing the cause of deterioration, it is expected to utilize machine learning technology, especially deep learning. Although deterioration of the rubber materials can be observed from electron microscope images, it is difficult to obtain a large number of deteriorated data. Hence, we solve the above problem by using feature representations based on deep learning. Deep convolutional neural network (DCNN) can learn high representation features from target data sources, and extracted features from pre-trained DCNNs have been used by many researchers. In this paper, we can obtain features based on deep learning from rubber materials by using such pre-trained DCNNs. Finally, we can estimate deteriorated regions based on anomaly detection by using the obtained features. In this paper, we verify feature representations extracted from DCNN models to improve the estimation performance. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Region estimation / Anomaly detection / Deep learning / Feature representation / Rubber materials / / / |
Reference Info. |
IEICE Tech. Rep. |
Paper # |
|
Date of Issue |
|
ISSN |
|
Download PDF |
|
Conference Information |
Committee |
IE ITS ITE-MMS ITE-ME ITE-AIT |
Conference Date |
2021-02-18 - 2021-02-19 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Image Processing, etc. |
Paper Information |
Registration To |
ITE-ME |
Conference Code |
2021-02-IE-ITS-MMS-ME-AIT |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A Note on Estimation of Deteriorated Regions Based on Anomaly Detection from Rubber Material Electron Microscope Images |
Sub Title (in English) |
Verification of Feature Representations Extracted from Deep Learning Models |
Keyword(1) |
Region estimation |
Keyword(2) |
Anomaly detection |
Keyword(3) |
Deep learning |
Keyword(4) |
Feature representation |
Keyword(5) |
Rubber materials |
Keyword(6) |
|
Keyword(7) |
|
Keyword(8) |
|
1st Author's Name |
Masanao Matsumoto |
1st Author's Affiliation |
Hokkaido University (Hokkaido Univ) |
2nd Author's Name |
Ren Togo |
2nd Author's Affiliation |
Hokkaido University (Hokkaido Univ) |
3rd Author's Name |
Takahiro Ogawa |
3rd Author's Affiliation |
Hokkaido University (Hokkaido Univ) |
4th Author's Name |
Miki Haseyama |
4th Author's Affiliation |
Hokkaido University (Hokkaido Univ) |
5th Author's Name |
|
5th Author's Affiliation |
() |
6th Author's Name |
|
6th Author's Affiliation |
() |
7th Author's Name |
|
7th Author's Affiliation |
() |
8th Author's Name |
|
8th Author's Affiliation |
() |
9th Author's Name |
|
9th Author's Affiliation |
() |
10th Author's Name |
|
10th Author's Affiliation |
() |
11th Author's Name |
|
11th Author's Affiliation |
() |
12th Author's Name |
|
12th Author's Affiliation |
() |
13th Author's Name |
|
13th Author's Affiliation |
() |
14th Author's Name |
|
14th Author's Affiliation |
() |
15th Author's Name |
|
15th Author's Affiliation |
() |
16th Author's Name |
|
16th Author's Affiliation |
() |
17th Author's Name |
|
17th Author's Affiliation |
() |
18th Author's Name |
|
18th Author's Affiliation |
() |
19th Author's Name |
|
19th Author's Affiliation |
() |
20th Author's Name |
|
20th Author's Affiliation |
() |
Speaker |
Author-1 |
Date Time |
2021-02-18 14:50:00 |
Presentation Time |
25 minutes |
Registration for |
ITE-ME |
Paper # |
|
Volume (vol) |
vol.120 |
Number (no) |
|
Page |
|
#Pages |
|
Date of Issue |
|