{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T11:33:01Z","timestamp":1742988781746,"version":"3.40.3"},"publisher-location":"Cham","reference-count":44,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031781650"},{"type":"electronic","value":"9783031781667"}],"license":[{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-78166-7_19","type":"book-chapter","created":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T21:34:23Z","timestamp":1733088863000},"page":"287-303","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Probabilistic Fusion Framework Combining CNNs and\u00a0Graphical Models for\u00a0Multiresolution Satellite and\u00a0UAV Image Classification"],"prefix":"10.1007","author":[{"given":"Martina","family":"Pastorino","sequence":"first","affiliation":[]},{"given":"Gabriele","family":"Moser","sequence":"additional","affiliation":[]},{"given":"Fabien","family":"Guerra","sequence":"additional","affiliation":[]},{"given":"Sebastiano B.","family":"Serpico","sequence":"additional","affiliation":[]},{"given":"Josiane","family":"Zerubia","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,2]]},"reference":[{"key":"19_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.srs.2021.100019","volume":"3","author":"E Alvarez-Vanhard","year":"2021","unstructured":"Alvarez-Vanhard, E., Corpetti, T., Houet, T.: UAV & satellite synergies for optical remote sensing applications: a literature review. Sci. Remote Sens. 3, 100019 (2021)","journal-title":"Sci. Remote Sens."},{"issue":"3","key":"19_CR2","doi-asserted-by":"publisher","first-page":"1367","DOI":"10.1109\/36.763301","volume":"37","author":"J Benediktsson","year":"1999","unstructured":"Benediktsson, J., Kanellopoulos, I.: Classification of multisource and hyperspectral data based on decision fusion. IEEE Trans. Geosci. Remote Sens. 37(3), 1367\u20131377 (1999)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"2","key":"19_CR3","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1109\/34.67641","volume":"13","author":"C Bouman","year":"1991","unstructured":"Bouman, C., Liu, B.: Multiple resolution segmentation of textured images. IEEE Trans. Pattern Anal. Mach. Intell. 13(2), 99\u2013113 (1991)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"19_CR4","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"issue":"10","key":"19_CR5","doi-asserted-by":"publisher","first-page":"2291","DOI":"10.1109\/TGRS.2002.802476","volume":"40","author":"G Briem","year":"2002","unstructured":"Briem, G., Benediktsson, J., Sveinsson, J.: Multiple classifiers applied to multisource remote sensing data. IEEE Trans. Geosci. Remote Sens. 40(10), 2291\u20132299 (2002)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"19_CR6","doi-asserted-by":"publisher","first-page":"1495","DOI":"10.1109\/TIP.2003.819237","volume":"12","author":"A Cole-Rhodes","year":"2003","unstructured":"Cole-Rhodes, A., Johnson, K., LeMoigne, J., Zavorin, I.: Multiresolution registration of remote sensing imagery by optimization of mutual information using a stochastic gradient. IEEE Trans. Image Process. 12, 1495\u20131511 (2003)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Series B (Stat. Methodol.) 39(1), 1\u201338 (1977)","DOI":"10.1111\/j.2517-6161.1977.tb01600.x"},{"key":"19_CR8","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.isprsjprs.2017.10.012","volume":"134","author":"T Esch","year":"2017","unstructured":"Esch, T., et al.: Breaking new ground in mapping human settlements from space - the global urban footprint. ISPRS J. Photogramm. Remote. Sens. 134, 30\u201342 (2017)","journal-title":"ISPRS J. Photogramm. Remote. Sens."},{"key":"19_CR9","first-page":"1","volume":"21","author":"W Fang","year":"2024","unstructured":"Fang, W., Fu, Y., Sheng, V.S.: Dual backbone interaction network for burned area segmentation in optical remote sensing images. IEEE Geosci. Remote Sens. Lett. 21, 1\u20135 (2024)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"9","key":"19_CR10","doi-asserted-by":"publisher","first-page":"1560","DOI":"10.1109\/JPROC.2015.2449668","volume":"103","author":"L G\u00f3mez-Chova","year":"2015","unstructured":"G\u00f3mez-Chova, L., Tuia, D., Moser, G., Camps-Valls, G.: Multimodal classification of remote sensing images: a review and future directions. Proc. IEEE 103(9), 1560\u20131584 (2015)","journal-title":"Proc. IEEE"},{"issue":"5","key":"19_CR11","doi-asserted-by":"publisher","first-page":"1339","DOI":"10.1080\/01431160701736489","volume":"29","author":"J Hyypp\u00e4","year":"2008","unstructured":"Hyypp\u00e4, J., Hyypp\u00e4, H., Leckie, D., Gougeon, F., Yu, X., Maltamo, M.: Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests. Int. J. Remote Sens. 29(5), 1339\u20131366 (2008)","journal-title":"Int. J. Remote Sens."},{"issue":"1\u20132","key":"19_CR12","first-page":"1","volume":"5","author":"Z Kato","year":"2012","unstructured":"Kato, Z., Zerubia, J.: Markov random fields in image segmentation. Found. Trends Signal Process. 5(1\u20132), 1\u2013155 (2012)","journal-title":"Found. Trends Signal Process."},{"issue":"1","key":"19_CR13","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1016\/S0167-8655(02)00270-2","volume":"24","author":"JB Kim","year":"2003","unstructured":"Kim, J.B., Kim, H.J.: Multiresolution-based watersheds for efficient image segmentation. Pattern Recognit. Lett. 24(1), 473\u2013488 (2003)","journal-title":"Pattern Recognit. Lett."},{"issue":"6","key":"19_CR14","doi-asserted-by":"publisher","first-page":"1725","DOI":"10.1007\/s11222-020-09968-0","volume":"30","author":"E Kuhn","year":"2020","unstructured":"Kuhn, E., Matias, C., Rebafka, T.: Properties of the stochastic approximation EM algorithm with mini-batch sampling. Stat. Comput. 30(6), 1725\u20131739 (2020). https:\/\/doi.org\/10.1007\/s11222-020-09968-0","journal-title":"Stat. Comput."},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Lafert\u00e9, J.M., Heitz, F., Perez, P.: A multiresolution EM algorithm for unsupervised image classification. In: International Conference on Pattern Recognition (ICPR). vol.\u00a02, pp. 849\u2013853 (1996)","DOI":"10.1109\/ICPR.1996.547196"},{"issue":"3","key":"19_CR16","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1109\/83.826777","volume":"9","author":"JM Lafert\u00e9","year":"2000","unstructured":"Lafert\u00e9, J.M., P\u00e9rez, P., Heitz, F.: Discrete Markov image modeling and inference on the quadtree. IEEE Trans. Image Process. 9(3), 390\u2013404 (2000)","journal-title":"IEEE Trans. Image Process."},{"issue":"11","key":"19_CR17","doi-asserted-by":"publisher","first-page":"1186","DOI":"10.1109\/34.244679","volume":"15","author":"A Laine","year":"1993","unstructured":"Laine, A., Fan, J.: Texture classification by wavelet packet signatures. IEEE Trans. Pattern Anal. Mach. Intell. 15(11), 1186\u20131191 (1993)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"19_CR18","unstructured":"Li, S.Z.: Markov random field modeling in image analysis. Springer, 3rd edn. (2009)"},{"key":"19_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2024.3498868","volume":"62","author":"H Liu","year":"2024","unstructured":"Liu, H., et al.: Clusterformer for pine tree disease identification based on UAV remote sensing image segmentation. IEEE Trans. Geosci. Remote Sens. 62, 1\u201315 (2024)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"9","key":"19_CR20","doi-asserted-by":"publisher","first-page":"4317","DOI":"10.1109\/JBHI.2023.3285936","volume":"27","author":"S Liu","year":"2023","unstructured":"Liu, S., Cai, T., Tang, X., Wang, C.: MRL-Net: multi-scale representation learning network for COVID-19 lung CT image segmentation. IEEE J. Biomed. Health Inform. 27(9), 4317\u20134328 (2023)","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"19_CR21","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3431\u20133440 (2015)","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"19_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2022.3198508","volume":"60","author":"W Luan","year":"2022","unstructured":"Luan, W., Zhang, X., Xiao, P., Wang, H., Chen, S.: Binary and fractional MODIS snow cover mapping boosted by machine learning and big Landsat data. IEEE Trans. Geosci. Remote Sens. 60, 1\u201314 (2022)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"6","key":"19_CR23","doi-asserted-by":"publisher","first-page":"4972","DOI":"10.1109\/TGRS.2020.3015272","volume":"59","author":"M Luotamo","year":"2021","unstructured":"Luotamo, M., Mets\u00e4m\u00e4ki, S., Klami, A.: Multiscale cloud detection in remote sensing images using a dual convolutional neural network. IEEE Trans. Geosci. Remote Sens. 59(6), 4972\u20134983 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"19_CR24","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1109\/TNNLS.2022.3172183","volume":"35","author":"LT Luppino","year":"2024","unstructured":"Luppino, L.T., et al.: Code-aligned autoencoders for unsupervised change detection in multimodal remote sensing images. IEEE Trans. Neural Netw. Learn. Syst. 35(1), 60\u201372 (2024)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"19_CR25","unstructured":"Mallat, S.: A wavelet tour of signal processing \u2013 The sparse way. Academic Press, 3rd edn. (2009)"},{"issue":"7","key":"19_CR26","first-page":"3523","volume":"44","author":"S Minaee","year":"2022","unstructured":"Minaee, S., Boykov, Y., Porikli, F., Plaza, A., Kehtarnavaz, N., Terzopoulos, D.: Image segmentation using deep learning: a survey. IEEE Trans. Pattern Anal. Mach. Intell. 44(7), 3523\u20133542 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"19_CR27","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1109\/79.543975","volume":"13","author":"T Moon","year":"1996","unstructured":"Moon, T.: The expectation-maximization algorithm. IEEE Signal Process. Mag. 13(6), 47\u201360 (1996)","journal-title":"IEEE Signal Process. Mag."},{"issue":"7","key":"19_CR28","doi-asserted-by":"publisher","first-page":"2114","DOI":"10.1109\/TGRS.2009.2012407","volume":"47","author":"G Moser","year":"2009","unstructured":"Moser, G., Serpico, S.B.: Unsupervised change detection from multichannel SAR data by Markovian data fusion. IEEE Trans. Geosci. Remote Sens. 47(7), 2114\u20132128 (2009)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"5","key":"19_CR29","doi-asserted-by":"publisher","first-page":"849","DOI":"10.3390\/rs13050849","volume":"13","author":"M Pastorino","year":"2021","unstructured":"Pastorino, M., et al.: Multisensor and multiresolution remote sensing image classification through a causal hierarchical Markov framework and decision tree ensembles. Remote Sens. 13(5), 849 (2021)","journal-title":"Remote Sens."},{"issue":"5407116","key":"19_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2022.3141996","volume":"60","author":"M Pastorino","year":"2022","unstructured":"Pastorino, M., Moser, G., Serpico, S.B., Zerubia, J.: Semantic segmentation of remote-sensing images through fully convolutional neural networks and hierarchical probabilistic graphical models. IEEE Trans. Geosci. Remote Sens. 60(5407116), 1\u201316 (2022)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"7","key":"19_CR31","doi-asserted-by":"publisher","first-page":"1902","DOI":"10.1109\/TIP.2007.899612","volume":"16","author":"K Pyun","year":"2007","unstructured":"Pyun, K., Lim, J., Won, C.S., Gray, R.M.: Image segmentation using hidden Markov Gauss mixture models. IEEE Trans. Image Process. 16(7), 1902\u20131911 (2007)","journal-title":"IEEE Trans. Image Process."},{"issue":"7","key":"19_CR32","doi-asserted-by":"publisher","first-page":"1238","DOI":"10.1109\/83.847836","volume":"9","author":"M Rezaee","year":"2000","unstructured":"Rezaee, M., van der Zwet, P., Lelieveldt, B., van der Geest, R., Reiber, J.: A multiresolution image segmentation technique based on pyramidal segmentation and fuzzy clustering. IEEE Trans. Image Process. 9(7), 1238\u20131248 (2000)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR33","doi-asserted-by":"crossref","unstructured":"Richards, J.A.: Remote sensing digital image analysis: An introduction. Springer, 5th edn. (2013)","DOI":"10.1007\/978-3-642-30062-2"},{"key":"19_CR34","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2014 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"key":"19_CR35","first-page":"1","volume":"61","author":"P Song","year":"2023","unstructured":"Song, P., Li, J., An, Z., Fan, H., Fan, L.: CTMFNet: CNN and transformer multiscale fusion network of remote sensing urban scene imagery. IEEE Trans. Geosci. Remote Sens. 61, 1\u201314 (2023)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"19_CR36","doi-asserted-by":"crossref","unstructured":"Thoonen, G., Mahmood, Z., Peeters, S., Scheunders, P.: Multisource classification of color and hyperspectral images using color attribute profiles and composite decision fusion. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 5(2), 510\u2013521 (2012)","DOI":"10.1109\/JSTARS.2011.2168317"},{"key":"19_CR37","doi-asserted-by":"crossref","unstructured":"van Rijthoven, M., Balkenhol, M., Silina, K., van der Laak, J., Ciompi, F.: HookNet: multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images. Med. Image Anal. 68, 101890 (2021)","DOI":"10.1016\/j.media.2020.101890"},{"issue":"2","key":"19_CR38","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/S0167-8655(98)00129-9","volume":"20","author":"L Wang","year":"1999","unstructured":"Wang, L., Liu, J.: Texture classification using multiresolution Markov random field models. Pattern Recognit. Lett. 20(2), 171\u2013182 (1999)","journal-title":"Pattern Recognit. Lett."},{"key":"19_CR39","doi-asserted-by":"crossref","unstructured":"Wang, L., Zhang, C., Li, R., Duan, C., Meng, X., Atkinson, P.M.: Scale-aware neural network for semantic segmentation of multi-resolution remote sensing images. Remote Sens. 13(24), 5015 (2021)","DOI":"10.3390\/rs13245015"},{"issue":"12","key":"19_CR40","doi-asserted-by":"publisher","first-page":"3858","DOI":"10.1109\/TGRS.2007.898446","volume":"45","author":"B Waske","year":"2007","unstructured":"Waske, B., Benediktsson, J.A.: Fusion of support vector machines for classification of multisensor data. IEEE Trans. Geosci. Remote Sens. 45(12), 3858\u20133866 (2007)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"19_CR41","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1214\/aos\/1176346060","volume":"11","author":"CFJ Wu","year":"1983","unstructured":"Wu, C.F.J.: On the convergence properties of the EM algorithm. Annal. Stat. 11(1), 95\u2013103 (1983)","journal-title":"Annal. Stat."},{"key":"19_CR42","doi-asserted-by":"publisher","first-page":"770","DOI":"10.1109\/TIP.2005.847287","volume":"14","author":"I Zavorin","year":"2005","unstructured":"Zavorin, I., Moigne, J.: Use of multiresolution wavelet feature pyramids for automatic registration of multisensor imagery. IEEE Trans. Image Process. 14, 770\u201382 (2005)","journal-title":"IEEE Trans. Image Process."},{"key":"19_CR43","doi-asserted-by":"crossref","unstructured":"Zheng, G., Jiang, Z., Zhang, H., Yao, X.: Deep semantic segmentation of unmanned aerial vehicle remote sensing images based on fully convolutional neural network. Front. Earth Sci. 11, 1115805 (2023)","DOI":"10.3389\/feart.2023.1115805"},{"issue":"211","key":"19_CR44","first-page":"1","volume":"23","author":"F Zhou","year":"2022","unstructured":"Zhou, F., et al.: Efficient inference for dynamic flexible interactions of neural populations. J. Mach. Learn. Res. 23(211), 1\u201349 (2022)","journal-title":"J. Mach. Learn. Res."}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78166-7_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T23:37:37Z","timestamp":1733096257000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78166-7_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,2]]},"ISBN":["9783031781650","9783031781667"],"references-count":44,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78166-7_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,12,2]]},"assertion":[{"value":"2 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","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":"1 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}