MAPM:PolSAR Image Classification with Masked Autoencoder Based on Position Prediction and Memory Tokens Article Swipe
Jianlong Wang
,
Yingying Li
,
Dou Quan
,
Beibei Hou
,
Zhensong Wang
,
Haifeng Sima
,
Junding Sun
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/rs16224280
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/rs16224280
Deep learning methods have shown significant advantages in polarimetric synthetic aperture radar (PolSAR) image classification. However, their performances rely on a large number of labeled data. To alleviate this problem, this paper proposes a PolSAR image classification method with a Masked Autoencoder based on Position prediction and Memory tokens (MAPM). First, MAPM designs a Masked Autoencoder (MAE) based on the transformer for pre-training, which can boost feature learning and improve classification results based on the number of labeled samples. Secondly, since the transformer is relatively insensitive to the order of the input tokens, a position prediction strategy is introduced in the encoder part of the MAE. It can effectively capture subtle differences and discriminate complex, blurry boundaries in PolSAR images. In the fine-tuning stage, the addition of learnable memory tokens can improve classification performance. In addition, L1 loss is used for MAE optimization to enhance the robustness of the model to outliers in PolSAR data. Experimental results show the effectiveness and advantages of the proposed MAPM in PolSAR image classification. Specifically, MAPM achieves performance gains of about 1% in classification accuracy compared with existing methods.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs16224280
- https://www.mdpi.com/2072-4292/16/22/4280/pdf?version=1731827671
- OA Status
- gold
- Cited By
- 3
- References
- 49
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404501661
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4404501661Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/rs16224280Digital Object Identifier
- Title
-
MAPM:PolSAR Image Classification with Masked Autoencoder Based on Position Prediction and Memory TokensWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-11-17Full publication date if available
- Authors
-
Jianlong Wang, Yingying Li, Dou Quan, Beibei Hou, Zhensong Wang, Haifeng Sima, Junding SunList of authors in order
- Landing page
-
https://doi.org/10.3390/rs16224280Publisher landing page
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https://www.mdpi.com/2072-4292/16/22/4280/pdf?version=1731827671Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://www.mdpi.com/2072-4292/16/22/4280/pdf?version=1731827671Direct OA link when available
- Concepts
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Autoencoder, Computer science, Pattern recognition (psychology), Artificial intelligence, Position (finance), Artificial neural network, Finance, EconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3Per-year citation counts (last 5 years)
- References (count)
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49Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| primary_location.pdf_url | https://www.mdpi.com/2072-4292/16/22/4280/pdf?version=1731827671 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Remote Sensing |
| primary_location.landing_page_url | https://doi.org/10.3390/rs16224280 |
| publication_date | 2024-11-17 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W2103290993, https://openalex.org/W2989503313, https://openalex.org/W2079299474, https://openalex.org/W4308212078, https://openalex.org/W2126895410, https://openalex.org/W4353055574, https://openalex.org/W2793659031, https://openalex.org/W2597537214, https://openalex.org/W2905138651, https://openalex.org/W3000122775, https://openalex.org/W2098204899, https://openalex.org/W2074866567, https://openalex.org/W2037095848, https://openalex.org/W2097272115, https://openalex.org/W2133989913, https://openalex.org/W1969674753, https://openalex.org/W1920235975, https://openalex.org/W2179290474, https://openalex.org/W2370317051, https://openalex.org/W1917898038, https://openalex.org/W2098850102, https://openalex.org/W2969662039, https://openalex.org/W2595106450, https://openalex.org/W2883624990, https://openalex.org/W4311217720, https://openalex.org/W2062059528, https://openalex.org/W4213019189, https://openalex.org/W4309299023, https://openalex.org/W4226512186, https://openalex.org/W4206522033, https://openalex.org/W4296350506, https://openalex.org/W4379469637, https://openalex.org/W4313156423, https://openalex.org/W4387546514, https://openalex.org/W4292970091, https://openalex.org/W2939600327, https://openalex.org/W3080997787, https://openalex.org/W3171125843, https://openalex.org/W4306194616, https://openalex.org/W3132607382, https://openalex.org/W2039240409, https://openalex.org/W4285794683, https://openalex.org/W6698971750, https://openalex.org/W4386076539, https://openalex.org/W4312642299, https://openalex.org/W2345852998, https://openalex.org/W4292189877, https://openalex.org/W2909431601, https://openalex.org/W2314720829 |
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| corresponding_author_ids | https://openalex.org/A5100666568 |
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| corresponding_institution_ids | https://openalex.org/I4210166499 |
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