{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T15:30:26Z","timestamp":1782315026781,"version":"3.54.5"},"reference-count":15,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Geosci. Remote Sensing Lett."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/lgrs.2025.3583475","type":"journal-article","created":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T13:46:14Z","timestamp":1750945574000},"page":"1-5","source":"Crossref","is-referenced-by-count":7,"title":["CPL-PL: Contrapositive Learning-Based Pseudo-Labeling for Semi-Supervised Scene Classification in Remote Sensing Images"],"prefix":"10.1109","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6059-3544","authenticated-orcid":false,"given":"G.","family":"Swetha","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, IIT Hyderabad, Hyderabad, Telangana, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2980-9175","authenticated-orcid":false,"given":"Rajeshreddy","family":"Datla","sequence":"additional","affiliation":[{"name":"Advanced Data Processing Research Institute (ADRIN), Department of Space, Secunderabad, Telangana, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1645-8502","authenticated-orcid":false,"given":"Sobhan","family":"Babu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, IIT Hyderabad, Hyderabad, Telangana, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7316-0836","authenticated-orcid":false,"given":"C. Krishna","family":"Mohan","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, IIT Hyderabad, Hyderabad, Telangana, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.127679"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9533648"},{"key":"ref3","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. NeurIPS","author":"Tarvainen"},{"key":"ref4","first-page":"5050","article-title":"MixMatch: A holistic approach to semi-supervised learning","volume-title":"Proc. NeurIPS","author":"Berthelot"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.isprsjprs.2020.06.014","article-title":"X-ModalNet: A semi-supervised deep cross-modal network for classification of remote sensing data","volume":"167","author":"Hong","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref6","first-page":"896","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"Proc. ICML Workshop, Challenges Represent. Learn.","author":"Lee"},{"key":"ref7","first-page":"18408","article-title":"FlexMatch: Boosting semi-supervised learning with curriculum pseudo labeling","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Zhang"},{"key":"ref8","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","volume-title":"Proc. ICML","author":"Chen"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/1869790.1869829"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2017.2675998"},{"key":"ref12","first-page":"596","article-title":"FixMatch: Simplifying semisupervised learning with consistency and confidence","volume-title":"Proc. 34th Int. Conf. Neural Inf. Process. Syst.","author":"Sohn"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-14903-0_24"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3414122"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2021.3126082"}],"container-title":["IEEE Geoscience and Remote Sensing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8859\/10764750\/11052310.pdf?arnumber=11052310","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T18:45:42Z","timestamp":1766429142000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11052310\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":15,"URL":"https:\/\/doi.org\/10.1109\/lgrs.2025.3583475","relation":{},"ISSN":["1545-598X","1558-0571"],"issn-type":[{"value":"1545-598X","type":"print"},{"value":"1558-0571","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}