{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:14:54Z","timestamp":1774120494498,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":23,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819755967","type":"print"},{"value":"9789819755974","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-5597-4_16","type":"book-chapter","created":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T09:10:06Z","timestamp":1722503406000},"page":"181-192","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Superpixel-Based Dual-Neighborhood Contrastive Graph Autoencoder for Deep Subspace Clustering of Hyperspectral Image"],"prefix":"10.1007","author":[{"given":"Junhong","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renxiang","family":"Guan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhang","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaowen","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zihao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanyan","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziwei","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianju","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,2]]},"reference":[{"issue":"7","key":"16_CR1","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1109\/TPAMI.2002.1017616","volume":"24","author":"T Kanungo","year":"2002","unstructured":"Kanungo, T., Mount, D.M., Netanyahu, N.S., Piatko, C.D., Silverman, R., Wu, A.Y.: An efficient k-means clustering algorithm: analysis and implementation. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 881\u2013892 (2002)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"16_CR2","doi-asserted-by":"publisher","first-page":"831","DOI":"10.1109\/JSTARS.2013.2244851","volume":"6","author":"S Niazmardi","year":"2013","unstructured":"Niazmardi, S., Homayouni, S., Safari, A.: An improved FCM algorithm based on the SVDD for unsupervised hyperspectral data classification. IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. 6(2), 831\u2013839 (2013)","journal-title":"IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens."},{"issue":"11","key":"16_CR3","doi-asserted-by":"publisher","first-page":"2765","DOI":"10.1109\/TPAMI.2013.57","volume":"35","author":"E Elhamifar","year":"2013","unstructured":"Elhamifar, E., Vidal, R.: Sparse subspace clustering: algorithm, theory, and applications. IEEE Trans. Pattern Anal. Mach. Intell. 35(11), 2765\u20132781 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"16_CR4","unstructured":"Matsushima, S., Brbic, M.: Selective sampling-based scalable sparse subspace clustering. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"key":"16_CR5","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.patrec.2013.08.006","volume":"43","author":"R Vidal","year":"2014","unstructured":"Vidal, R., Favaro, P.: Low rank subspace clustering (LRSC). Pattern Recogn. Lett. 43, 47\u201361 (2014)","journal-title":"Pattern Recogn. Lett."},{"issue":"13","key":"16_CR6","doi-asserted-by":"publisher","first-page":"3216","DOI":"10.3390\/rs14133216","volume":"14","author":"R Guan","year":"2022","unstructured":"Guan, R., Li, Z., Li, T., Li, X., Yang, J., Chen, W.: Classification of heterogeneous mining areas based on ResCapsNet and Gaofen-5 imagery. Remote Sens. 14(13), 3216 (2022)","journal-title":"Remote Sens."},{"issue":"23","key":"16_CR7","doi-asserted-by":"publisher","first-page":"5483","DOI":"10.3390\/rs15235483","volume":"15","author":"J Liu","year":"2023","unstructured":"Liu, J., Guan, R., Li, Z., Zhang, J., Hu, Y., Wang, X.: Adaptive multi-feature fusion graph convolutional network for hyperspectral image classification. Remote Sens. 15(23), 5483 (2023)","journal-title":"Remote Sens."},{"key":"16_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1007\/978-3-030-01264-9_9","volume-title":"Computer Vision \u2013 ECCV 2018","author":"M Caron","year":"2018","unstructured":"Caron, M., Bojanowski, P., Joulin, A., Douze, M.: Deep clustering for unsupervised learning of visual features. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) Computer Vision \u2013 ECCV 2018. LNCS, vol. 11218, pp. 139\u2013156. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01264-9_9"},{"key":"16_CR9","doi-asserted-by":"crossref","unstructured":"Zeng, M., Cai, Y., Liu, X., Cai, Z., Li, X.: Spectral-spatial clustering of hyperspectral image based on Laplacian regularized deep subspace clustering. In: IGARSS 2019\u20132019 IEEE International Geoscience and Remote Sensing Symposium, pp. 2694\u20132697. IEEE (2019)","DOI":"10.1109\/IGARSS.2019.8898947"},{"key":"16_CR10","doi-asserted-by":"crossref","unstructured":"Guan, R., Li, Z., Song, C., Yu, G., Li, X., Feng, R.: S2RC-GCN: a spatial-spectral reliable contrastive graph convolutional network for complex land cover classification using hyperspectral images. arXiv preprint arXiv:2404.00964 (2024)","DOI":"10.1109\/IJCNN60899.2024.10650629"},{"issue":"5","key":"16_CR11","doi-asserted-by":"publisher","first-page":"4191","DOI":"10.1109\/TGRS.2020.3018135","volume":"59","author":"Y Cai","year":"2020","unstructured":"Cai, Y., Zhang, Z., Cai, Z., Liu, X., Jiang, X., Yan, Q.: Graph convolutional subspace clustering: a robust subspace clustering framework for hyperspectral image. IEEE Trans. Geosci. Remote Sens. 59(5), 4191\u20134202 (2020)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"12","key":"16_CR12","doi-asserted-by":"publisher","first-page":"8500","DOI":"10.1109\/TCSVT.2022.3196679","volume":"32","author":"Y Zhang","year":"2022","unstructured":"Zhang, Y., Wang, Y., Chen, X., Jiang, X., Zhou, Y.: Spectral\u2013spatial feature extraction with dual graph autoencoder for hyperspectral image clustering. IEEE Trans. Circuits Syst. Video Technol. 32(12), 8500\u20138511 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"16_CR13","doi-asserted-by":"crossref","unstructured":"Guan, R., Li, Z., Li, X., Tang, C.: Pixel-superpixel contrastive learning and pseudo-label correction for hyperspectral image clustering. In: ICASSP 2024\u20132024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6795\u20136799. IEEE (2024)","DOI":"10.1109\/ICASSP48485.2024.10447080"},{"key":"16_CR14","doi-asserted-by":"crossref","unstructured":"Guan, R., et al.: Contrastive multi-view subspace clustering of hyperspectral images based on graph convolutional networks. IEEE Trans. Geosci. Remote Sens. 62, 1\u201314 (2024)","DOI":"10.1109\/TGRS.2024.3370633"},{"key":"16_CR15","first-page":"1","volume":"60","author":"S Liu","year":"2022","unstructured":"Liu, S., Wang, H.: Graph convolutional optimal transport for hyperspectral image spectral clustering. IEEE Trans. Geosci. Remote Sens. 60, 1\u201313 (2022)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"16_CR16","doi-asserted-by":"crossref","unstructured":"Liu, M.Y., Tuzel, O., Ramalingam, S., Chellappa, R.: Entropy rate superpixel segmentation. In: CVPR 2011, pp. 2097\u20132104. IEEE (2011)","DOI":"10.1109\/CVPR.2011.5995323"},{"issue":"2","key":"16_CR17","doi-asserted-by":"publisher","first-page":"839","DOI":"10.1109\/TNNLS.2020.3029523","volume":"33","author":"J Jiang","year":"2020","unstructured":"Jiang, J., Ma, J., Liu, X.: Multilayer spectral\u2013spatial graphs for label noisy robust hyperspectral image classification. IEEE Trans. Neural Netw. Learn. Syst. 33(2), 839\u2013852 (2020)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"16_CR18","first-page":"1","volume":"60","author":"Y Cai","year":"2022","unstructured":"Cai, Y., et al.: Superpixel contracted neighborhood contrastive subspace clustering network for hyperspectral images. IEEE Trans. Geosci. Remote Sens. 60, 1\u201313 (2022)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"16_CR19","unstructured":"Sohn, K.: Improved deep metric learning with multi-class N-pair loss objective. In: Advances in Neural Information Processing Systems, vol. 29 (2016)"},{"key":"16_CR20","doi-asserted-by":"publisher","first-page":"6518","DOI":"10.1109\/JSTARS.2022.3198137","volume":"15","author":"KR Shahi","year":"2022","unstructured":"Shahi, K.R., Ghamisi, P., Rasti, B., Gloaguen, R., Scheunders, P.: MS2A-Net: multiscale spectral\u2013spatial association network for hyperspectral image clustering. IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. 15, 6518\u20136530 (2022)","journal-title":"IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens."},{"issue":"15","key":"16_CR21","doi-asserted-by":"publisher","first-page":"2421","DOI":"10.3390\/rs12152421","volume":"12","author":"K Rafiezadeh Shahi","year":"2020","unstructured":"Rafiezadeh Shahi, K., Khodadadzadeh, M., Tusa, L., Ghamisi, P., Tolosana-Delgado, R., Gloaguen, R.: Hierarchical sparse subspace clustering (HESSC): an automatic approach for hyperspectral image analysis. Remote Sens. 12(15), 2421 (2020)","journal-title":"Remote Sens."},{"key":"16_CR22","doi-asserted-by":"crossref","unstructured":"Wei, L., Chen, Z., Yin, J., Zhu, C., Zhou, R., Liu, J.: Adaptive graph convolutional subspace clustering. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6262\u20136271 (2023)","DOI":"10.1109\/CVPR52729.2023.00606"},{"key":"16_CR23","doi-asserted-by":"crossref","unstructured":"Guo, X., Gao, L., Liu, X., Yin, J.: Improved deep embedded clustering with local structure preservation. In: IJCAI, vol. 17, pp. 1753\u20131759 (2017)","DOI":"10.24963\/ijcai.2017\/243"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5597-4_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T13:14:15Z","timestamp":1732540455000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5597-4_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819755967","9789819755974"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5597-4_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"2 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2024\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}