{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T18:57:31Z","timestamp":1774551451138,"version":"3.50.1"},"reference-count":51,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2024,11,17]],"date-time":"2024-11-17T00:00:00Z","timestamp":1731801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62201201"],"award-info":[{"award-number":["62201201"]}]},{"name":"National Natural Science Foundation of China","award":["62201407"],"award-info":[{"award-number":["62201407"]}]},{"name":"National Natural Science Foundation of China","award":["B2022-15"],"award-info":[{"award-number":["B2022-15"]}]},{"name":"National Natural Science Foundation of China","award":["2022M722496"],"award-info":[{"award-number":["2022M722496"]}]},{"name":"Doctoral Foundation of Henan Polytechnic University","award":["62201201"],"award-info":[{"award-number":["62201201"]}]},{"name":"Doctoral Foundation of Henan Polytechnic University","award":["62201407"],"award-info":[{"award-number":["62201407"]}]},{"name":"Doctoral Foundation of Henan Polytechnic University","award":["B2022-15"],"award-info":[{"award-number":["B2022-15"]}]},{"name":"Doctoral Foundation of Henan Polytechnic University","award":["2022M722496"],"award-info":[{"award-number":["2022M722496"]}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["62201201"],"award-info":[{"award-number":["62201201"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["62201407"],"award-info":[{"award-number":["62201407"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["B2022-15"],"award-info":[{"award-number":["B2022-15"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2022M722496"],"award-info":[{"award-number":["2022M722496"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/rs16224280","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T06:06:54Z","timestamp":1731996414000},"page":"4280","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["MAPM:PolSAR Image Classification with Masked Autoencoder Based on Position Prediction and Memory Tokens"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8117-0631","authenticated-orcid":false,"given":"Jianlong","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454003, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6753-7265","authenticated-orcid":false,"given":"Yingying","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454003, China"}]},{"given":"Dou","family":"Quan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Beibei","family":"Hou","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454003, China"}]},{"given":"Zhensong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454003, China"}]},{"given":"Haifeng","family":"Sima","sequence":"additional","affiliation":[{"name":"School of Software, Henan Polytechnic University, Jiaozuo 454003, China"}]},{"given":"Junding","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454003, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1109\/TAES.1967.5408745","article-title":"Synthetic Aperture Radar","volume":"AES-3","author":"Brown","year":"1967","journal-title":"IEEE Trans. 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