Application of semi-supervised Mean Teacher to rock image segmentation
Accurate segmentation of rock images is crucial for studying the internal structure and properties of rocks. To address the issue of requiring a large number of labeled images for model training in traditional image segmentation methods, this paper proposes an improved semi-supervised Mean Teacher...
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| Format: | Article |
| Language: | English |
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Slovenian Society for Stereology and Quantitative Image Analysis
2025-01-01
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| Series: | Image Analysis and Stereology |
| Subjects: | |
| Online Access: | https://www.ias-iss.org/ojs/IAS/article/view/3279 |
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| _version_ | 1832570750660247552 |
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| author | Jiashan Li Yuxue Wang |
| author_facet | Jiashan Li Yuxue Wang |
| author_sort | Jiashan Li |
| collection | DOAJ |
| description |
Accurate segmentation of rock images is crucial for studying the internal structure and properties of rocks. To address the issue of requiring a large number of labeled images for model training in traditional image segmentation methods, this paper proposes an improved semi-supervised Mean Teacher algorithm based on ResNet34-UNet. This method achieves relatively accurate rock image segmentation using only a small amount of labeled data. Initially, we use ResNet34-UNet as the base model to create Student Model and Teacher Model with identical structures. Then, we introduce self-attention mechanism into the semi-supervised Mean Teacher algorithm to further enhance its performance in rock image segmentation. Finally, by comparing the performance of supervised and semi-supervised Mean Teacher algorithms on image segmentation tasks, we validate the effectiveness of semi-supervised learning in rock image segmentation.
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| format | Article |
| id | doaj-art-0e03911704ef4d8ab7edc783f46e6010 |
| institution | Kabale University |
| issn | 1580-3139 1854-5165 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Slovenian Society for Stereology and Quantitative Image Analysis |
| record_format | Article |
| series | Image Analysis and Stereology |
| spelling | doaj-art-0e03911704ef4d8ab7edc783f46e60102025-02-02T14:14:37ZengSlovenian Society for Stereology and Quantitative Image AnalysisImage Analysis and Stereology1580-31391854-51652025-01-0110.5566/ias.3279Application of semi-supervised Mean Teacher to rock image segmentationJiashan Li0Yuxue Wang1Northeast Petroleum UniversityNortheast Petroleum University Accurate segmentation of rock images is crucial for studying the internal structure and properties of rocks. To address the issue of requiring a large number of labeled images for model training in traditional image segmentation methods, this paper proposes an improved semi-supervised Mean Teacher algorithm based on ResNet34-UNet. This method achieves relatively accurate rock image segmentation using only a small amount of labeled data. Initially, we use ResNet34-UNet as the base model to create Student Model and Teacher Model with identical structures. Then, we introduce self-attention mechanism into the semi-supervised Mean Teacher algorithm to further enhance its performance in rock image segmentation. Finally, by comparing the performance of supervised and semi-supervised Mean Teacher algorithms on image segmentation tasks, we validate the effectiveness of semi-supervised learning in rock image segmentation. https://www.ias-iss.org/ojs/IAS/article/view/3279Image segmentationResNetRock imageSelf-attentionSemi-supervised learningUnet |
| spellingShingle | Jiashan Li Yuxue Wang Application of semi-supervised Mean Teacher to rock image segmentation Image Analysis and Stereology Image segmentation ResNet Rock image Self-attention Semi-supervised learning Unet |
| title | Application of semi-supervised Mean Teacher to rock image segmentation |
| title_full | Application of semi-supervised Mean Teacher to rock image segmentation |
| title_fullStr | Application of semi-supervised Mean Teacher to rock image segmentation |
| title_full_unstemmed | Application of semi-supervised Mean Teacher to rock image segmentation |
| title_short | Application of semi-supervised Mean Teacher to rock image segmentation |
| title_sort | application of semi supervised mean teacher to rock image segmentation |
| topic | Image segmentation ResNet Rock image Self-attention Semi-supervised learning Unet |
| url | https://www.ias-iss.org/ojs/IAS/article/view/3279 |
| work_keys_str_mv | AT jiashanli applicationofsemisupervisedmeanteachertorockimagesegmentation AT yuxuewang applicationofsemisupervisedmeanteachertorockimagesegmentation |