E-resources
Peer reviewed
-
Lei, Meng; Rao, Zhongyu; Wang, Hongdong; Chen, Yilin; Zou, Liang; Yu, Han
Fuel (Guildford), 06/2021, Volume: 294Journal Article
Display omitted •An effective metric is proposed to quantify the maceral composition of coal.•The task of maceral group identification is defined as a semantic segmentation task.•The proposed end-to-end way bypasses the steps limiting the traditional strategies. Correct identification macerals is important for analyzing petrographic characteristics of coal. Traditional methods based on manual measurement are time-consuming and physically demanding. Thus, automation of this process is highly desirable. However, currently available machine learning-based methods mostly depend on handcrafted features, and do not work in analyzing complex samples. There is still much room to enhance the robustness and generalization ability for these automatic methods. To address these issues, we interpret the task of maceral group identification as a semantic segmentation task. In this study, we design an improved U-net model with enhanced attention gates, and evaluate the performance with various encoder backbones. Experimental results on 89 photomicrographs indicate that the proposed method achieves the state-of-the-art segmentation accuracy of 91.56%. The model achieves mean absolute errors of 5.95%, 4.43% and 2.19% for the predicted proportion of vitrinite, inertinite and liptinite, respectively. It shows that the improved U-net model has significant potential for automating accurate identification of maceral groups.
![loading ... loading ...](themes/default/img/ajax-loading.gif)
Shelf entry
Permalink
- URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
Year | Impact factor | Edition | Category | Classification | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Select the library membership card:
If the library membership card is not in the list,
add a new one.
DRS, in which the journal is indexed
Database name | Field | Year |
---|
Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
---|
Source: Personal bibliographies
and: SICRIS
The material is available in full text. If you wish to order the material anyway, click the Continue button.