{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:28:07Z","timestamp":1740122887068,"version":"3.37.3"},"reference-count":78,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T00:00:00Z","timestamp":1686355200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T00:00:00Z","timestamp":1686355200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["3132019340"],"award-info":[{"award-number":["3132019340"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["3132019200"],"award-info":[{"award-number":["3132019200"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006579","name":"Ministry of Industry and Information Technology of the People\u2019s Republic of China","doi-asserted-by":"publisher","award":["MC-201902-C01"],"award-info":[{"award-number":["MC-201902-C01"]}],"id":[{"id":"10.13039\/501100006579","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s11042-023-15519-2","type":"journal-article","created":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T08:03:21Z","timestamp":1686384201000},"page":"6521-6554","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A global-local feature adaptive fusion network for image scene classification"],"prefix":"10.1007","volume":"83","author":[{"given":"Guangrui","family":"Lv","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1213-7691","authenticated-orcid":false,"given":"Lili","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenwen","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenhai","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,6,10]]},"reference":[{"key":"15519_CR1","doi-asserted-by":"crossref","unstructured":"Anwer RM, Khan FS, van de Weijer J et al (2018) Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification. ISPRS J Photogrammetry Rem Sens 138:74\u201385","DOI":"10.1016\/j.isprsjprs.2018.01.023"},{"key":"15519_CR2","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.future.2020.08.005","volume":"115","author":"ME Basiri","year":"2021","unstructured":"Basiri ME, Nemati S, Abdar M et al (2021) ABCDM: an attention-based bidirectional CNN-RNN deep model for sentiment analysis. Futur Gener Comput Syst 115:279\u2013294","journal-title":"Futur Gener Comput Syst"},{"key":"15519_CR3","first-page":"404","volume-title":"Surf: speeded up robust features, European conference on computer vision","author":"H Bay","year":"2006","unstructured":"Bay H, Tuytelaars T, Van Gool L (2006) Surf: speeded up robust features, European conference on computer vision. Springer, Berlin, pp 404\u2013417"},{"key":"15519_CR4","doi-asserted-by":"crossref","unstructured":"Bi Q, Qin K, Li Z et al (2019) Multiple instance dense connected convolution neural network for aerial image scene classification. In: 2019 IEEE International conference on image processing (ICIP). IEEE, pp 2501\u20132505","DOI":"10.1109\/ICIP.2019.8803322"},{"issue":"9","key":"15519_CR5","doi-asserted-by":"crossref","first-page":"1603","DOI":"10.1109\/LGRS.2019.2949930","volume":"17","author":"Q Bi","year":"2019","unstructured":"Bi Q, Qin K, Zhang H et al (2019) APDC-Net: attention pooling-based convolutional network for aerial scene classification. IEEE Geosci Rem Sens Lett 17(9):1603\u20131607","journal-title":"IEEE Geosci Rem Sens Lett"},{"key":"15519_CR6","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1016\/j.neucom.2019.11.068","volume":"377","author":"Q Bi","year":"2020","unstructured":"Bi Q, Qin K, Zhang H (2020) RADC-Net: a residual attention based convolution network for aerial scene classification. Neurocomputing 377:345\u2013359","journal-title":"Neurocomputing"},{"key":"15519_CR7","doi-asserted-by":"crossref","first-page":"4911","DOI":"10.1109\/TIP.2020.2975718","volume":"29","author":"Q Bi","year":"2020","unstructured":"Bi Q, Qin K, Li Z et al (2020) A multiple-instance densely-connected ConvNet for aerial scene classification. IEEE Trans Image Process 29:4911\u20134926","journal-title":"IEEE Trans Image Process"},{"key":"15519_CR8","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei DM, Ng AY, Jordan MI (2003) Latent Dirichlet allocation. J Mach Learn Res 3:993\u20131022","journal-title":"J Mach Learn Res"},{"key":"15519_CR9","unstructured":"Chen Y (2015) Convolutional neural network for sentence classification. University of Waterloo"},{"key":"15519_CR10","doi-asserted-by":"crossref","unstructured":"Cheng G, Ma C, Zhou P et al (2016) Scene classification of high resolution remote sensing images using convolutional neural networks. In: 2016 IEEE International geoscience and remote sensing symposium (IGARSS). IEEE, pp 767\u2013770","DOI":"10.1109\/IGARSS.2016.7729193"},{"issue":"99","key":"15519_CR11","first-page":"1","volume":"PP","author":"G Cheng","year":"2020","unstructured":"Cheng G, Xie X, Han J et al (2020) Remote sensing image scene classification meets deep learning: challenges, methods, benchmarks, and opportunities. IEEE J Selected Topics Appl Earth Observ Rem Sens PP(99):1\u20131","journal-title":"IEEE J Selected Topics Appl Earth Observ Rem Sens"},{"key":"15519_CR12","doi-asserted-by":"crossref","unstructured":"Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE computer society conference on computer vision and pattern recognition (CVPR\u201905), vol 1. IEEE, pp 886\u2013893","DOI":"10.1109\/CVPR.2005.177"},{"issue":"11","key":"15519_CR13","doi-asserted-by":"crossref","first-page":"2049","DOI":"10.1109\/TMM.2015.2477042","volume":"17","author":"C Ding","year":"2015","unstructured":"Ding C, Tao D (2015) Robust face recognition via multimodal deep face representation. IEEE Trans Multimed 17(11):2049\u20132058","journal-title":"IEEE Trans Multimed"},{"key":"15519_CR14","first-page":"5","volume":"39","author":"L Dong","year":"2020","unstructured":"Dong L, Zhang T, Ma D et al (2020) Maritime background infrared imagery classification based on histogram of oriented gradient and local contrast features. Journal of Infrared and Millimeter Waves 39:5","journal-title":"Journal of Infrared and Millimeter Waves"},{"key":"15519_CR15","unstructured":"Dosovitskiy A, Beyer L, Kolesnikov A et al (2020) An image is worth 16x16 words: transformers for image recognition at scale, arXiv:2010.11929"},{"key":"15519_CR16","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1109\/LSP.2021.3107209","volume":"28","author":"Y Feng","year":"2021","unstructured":"Feng Y, Chen F, Ji Y, et al. (2021) Efficient cross-modality graph reasoning for RGB-infrared person re-identification. IEEE Signal Process Lett 28:1425\u20131429","journal-title":"IEEE Signal Process Lett"},{"key":"15519_CR17","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S et al (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"issue":"1","key":"15519_CR18","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1023\/A:1007617005950","volume":"42","author":"T Hofmann","year":"2001","unstructured":"Hofmann T (2001) Unsupervised learning by probabilistic latent semantic analysis. Mach Learn 42(1):177\u2013196","journal-title":"Mach Learn"},{"key":"15519_CR19","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7132\u20137141","DOI":"10.1109\/CVPR.2018.00745"},{"key":"15519_CR20","doi-asserted-by":"crossref","unstructured":"Hu X, Yang K, Fei L et al (2019) Acnet: attention based network to exploit complementary features for rgbd semantic segmentation. In: IEEE International conference on image processing (ICIP). IEEE, pp 1440\u20131444","DOI":"10.1109\/ICIP.2019.8803025"},{"issue":"14","key":"15519_CR21","doi-asserted-by":"crossref","first-page":"1687","DOI":"10.3390\/rs11141687","volume":"11","author":"H Huang","year":"2019","unstructured":"Huang H, Xu K (2019) Combing triple-part features of convolutional neural networks for scene classification in remote sensing. Remote Sens 11(14):1687","journal-title":"Remote Sens"},{"key":"15519_CR22","first-page":"730","volume-title":"Randomized spatial partition for scene recognition, European conference on computer vision","author":"Y Jiang","year":"2012","unstructured":"Jiang Y, Yuan J, Yu G (2012) Randomized spatial partition for scene recognition, European conference on computer vision. Springer, Berlin, pp 730\u2013743"},{"key":"15519_CR23","doi-asserted-by":"crossref","unstructured":"Jgou H, Douze M, Schmid C et al (2010) Aggregating local descriptors into a compact image representation. In: 2010 IEEE computer society conference on computer vision and pattern recognition. IEEE, pp 3304\u20133311","DOI":"10.1109\/CVPR.2010.5540039"},{"key":"15519_CR24","doi-asserted-by":"crossref","unstructured":"Li LJ, Li FF (2007) What, where and who? Classifying events by scene and object recognition Computer Vision. In: Proc.of IEEE International conference on computer vision, pp 1\u20138","DOI":"10.1109\/ICCV.2007.4408872"},{"key":"15519_CR25","doi-asserted-by":"crossref","unstructured":"Li Q, Wu J, Tu Z (2013) Harvesting mid-level visual concepts from large-scale internet images. In: 2013 IEEE Conference on computer vision and pattern recognition, pp 851\u2013858","DOI":"10.1109\/CVPR.2013.115"},{"issue":"2","key":"15519_CR26","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1109\/MCSE.2018.108164530","volume":"20","author":"Q Li","year":"2018","unstructured":"Li Q, Peng Q, Yan C (2018) Multiple VLAD encoding of CNNs for image classification. Comput Sci Eng 20(2):52\u201363","journal-title":"Comput Sci Eng"},{"key":"15519_CR27","doi-asserted-by":"crossref","unstructured":"Lin D, Lu C, Liao R et al (2014) Learning important spatial pooling regions for scene classification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3726\u20133733","DOI":"10.1109\/CVPR.2014.476"},{"key":"15519_CR28","doi-asserted-by":"crossref","unstructured":"Liu Z, Lin Y, Cao Y et al (2021) Swin transformer: hierarchical vision transformer using shifted windows. International Conference on Computer Vision, 10012-10022","DOI":"10.1109\/ICCV48922.2021.00986"},{"issue":"2","key":"15519_CR29","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91\u2013110","journal-title":"Int J Comput Vis"},{"issue":"10","key":"15519_CR30","doi-asserted-by":"crossref","first-page":"7894","DOI":"10.1109\/TGRS.2019.2917161","volume":"57","author":"X Lu","year":"2019","unstructured":"Lu X, Sun H, Zheng X (2019) A feature aggregation convolutional neural network for remote sensing scene classification. IEEE Trans Geosci Remote Sens 57(10):7894\u20137906","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"24","key":"15519_CR31","first-page":"3006","volume":"11","author":"Y Lv","year":"2019","unstructured":"Lv Y, Zhang X, Xiong W et al (2019) An end-to-end local-global-fusion feature extraction network for remote sensing image scene classification. Rem Sens 2019 11(24):3006","journal-title":"Rem Sens 2019"},{"key":"15519_CR32","doi-asserted-by":"crossref","unstructured":"Ma J, Ma Q, Tang X et al (2020) Remote sensing scene classification based on global and local consistent network, IGARSS 2020-2020. In: IEEE International geoscience and remote sensing symposium. IEEE, pp 537\u2013540","DOI":"10.1109\/IGARSS39084.2020.9323281"},{"key":"15519_CR33","doi-asserted-by":"crossref","first-page":"7284","DOI":"10.1109\/JSTARS.2021.3096941","volume":"14","author":"K Ni","year":"2021","unstructured":"Ni K, Liu P, Wang P (2021) Compact global-local convolutional network with multifeature fusion and learning for scene classification in synthetic aperture radar imagery. IEEE J Selected Topics Appl Earth Observ Rem Sens 14:7284\u20137296","journal-title":"IEEE J Selected Topics Appl Earth Observ Rem Sens"},{"issue":"3","key":"15519_CR34","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1023\/A:1011139631724","volume":"42","author":"A Oliva","year":"2001","unstructured":"Oliva A, Torralba A (2001) Modeling the shape of the scene: a holistic representation of the spatial envelope. Int J Comput Vis 42(3):145\u2013175","journal-title":"Int J Comput Vis"},{"key":"15519_CR35","first-page":"143","volume-title":"Improving the fisher kernel for large-scale image classification, European conference on computer vision","author":"F Perronnin","year":"2010","unstructured":"Perronnin F, Snchez J, Mensink T (2010) Improving the fisher kernel for large-scale image classification, European conference on computer vision. Springer, Heidelberg, pp 143\u2013156"},{"issue":"4","key":"15519_CR36","doi-asserted-by":"crossref","first-page":"569","DOI":"10.3390\/rs13040569","volume":"13","author":"K Qi","year":"2021","unstructured":"Qi K, Yang C, Hu C et al (2021) Rotation invariance regularization for remote sensing image scene classification with convolutional neural networks[J]. Remote Sens 13(4):569","journal-title":"Remote Sens"},{"key":"15519_CR37","doi-asserted-by":"crossref","unstructured":"Rublee E, Rabaud V, Konolige K et al (2011) ORB: an efficient alternative to SIFT or SURF. In: 2011 International conference on computer vision. IEEE, pp 2564\u20132571","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"15519_CR38","first-page":"228","volume-title":"Latent pyramidal regions for recognizing scenes, European conference on computer vision","author":"F Sadeghi","year":"2012","unstructured":"Sadeghi F, Tappen M F (2012) Latent pyramidal regions for recognizing scenes, European conference on computer vision. Springer, Berlin, pp 228\u2013241"},{"issue":"5","key":"15519_CR39","doi-asserted-by":"crossref","first-page":"1953","DOI":"10.1109\/TIP.2014.2310123","volume":"23","author":"A Satpathy","year":"2014","unstructured":"Satpathy A, Jiang X, Eng HL (2014) LBP-based edge-texture features for object recognition. IEEE Trans Image Process 23(5):1953\u20131964","journal-title":"IEEE Trans Image Process"},{"issue":"8","key":"15519_CR40","doi-asserted-by":"crossref","first-page":"2395","DOI":"10.1080\/01431161.2011.608740","volume":"33","author":"G Sheng","year":"2012","unstructured":"Sheng G, Wen Y, Tao X et al (2012) High-resolution satellite scene classification using a sparse coding based multiple feature combination. Int J Remote Sens 33(8):2395\u20132412","journal-title":"Int J Remote Sens"},{"issue":"3","key":"15519_CR41","doi-asserted-by":"crossref","first-page":"433","DOI":"10.3390\/rs13030433","volume":"13","author":"J Shen","year":"2010","unstructured":"Shen J, Zhang T, Wang Y et al (2010) A dual-model architecture with grouping-attention-fusion for remote sensing scene classification. Remote Sens 13(3):433","journal-title":"Remote Sens"},{"key":"15519_CR42","doi-asserted-by":"crossref","first-page":"5194","DOI":"10.1109\/JSTARS.2020.3018307","volume":"13","author":"C Shi","year":"2020","unstructured":"Shi C, Wang T, Wang L (2020) Branch feature fusion convolution network for remote sensing scene classification. IEEE J Selected Topics Appl Earth Observ Rem Sens 13:5194\u20135210","journal-title":"IEEE J Selected Topics Appl Earth Observ Rem Sens"},{"issue":"1","key":"15519_CR43","doi-asserted-by":"crossref","first-page":"1237","DOI":"10.1007\/s11042-021-11354-5","volume":"81","author":"SR Shrinivasa","year":"2022","unstructured":"Shrinivasa SR, Prabhakar CJ (2022) Scene image classification based on visual words concatenation of local and global features. Multimed Tools Appl 81 (1):1237\u20131256","journal-title":"Multimed Tools Appl"},{"key":"15519_CR44","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. Computer Science"},{"key":"15519_CR45","doi-asserted-by":"crossref","unstructured":"Sitaula C, Xiang Y, Basnet A et al (2019) Tag-based semantic features for scene image classification. In: International conference on neural information processing. Springer, Cham, pp 90\u2013102","DOI":"10.1007\/978-3-030-36718-3_8"},{"key":"15519_CR46","first-page":"1","volume":"2020","author":"C Sitaula","year":"2020","unstructured":"Sitaula C, Xiang Y, Basnet A et al (2020) Hdf: hybrid deep features for scene image representation. International Joint Conference on Neural Networks (IJCNN) IEEE 2020:1\u20138","journal-title":"International Joint Conference on Neural Networks (IJCNN) IEEE"},{"key":"15519_CR47","doi-asserted-by":"crossref","first-page":"107470","DOI":"10.1016\/j.knosys.2021.107470","volume":"232","author":"C Sitaula","year":"2021","unstructured":"Sitaula C, Aryal S, Xiang Y et al (2021) Content and context features for scene image representation[J]. Knowl-Based Syst 232:107470","journal-title":"Knowl-Based Syst"},{"issue":"12","key":"15519_CR48","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1109\/34.895972","volume":"22","author":"AWM Smeulders","year":"2000","unstructured":"Smeulders AWM, Worring M, Santini S et al (2000) Content-based image retrieval at the end of the early years. IEEE Trans Pattern Anal Mach Intell 22(12):1349\u20131380","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"6","key":"15519_CR49","doi-asserted-by":"crossref","first-page":"1715","DOI":"10.1109\/TCSVT.2018.2848543","volume":"29","author":"N Sun","year":"2018","unstructured":"Sun N, Li W, Liu J et al (2018) Fusing object semantics and deep appearance features for scene recognition. IEEE Trans Circuits Syst Video Technol 29 (6):1715\u20131728","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"15519_CR50","doi-asserted-by":"crossref","unstructured":"Szegedy C, Liu W, Jia Y et al (2015) Going deeper with convolutions. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1\u20139","DOI":"10.1109\/CVPR.2015.7298594"},{"issue":"99","key":"15519_CR51","first-page":"1","volume":"PP","author":"H Sun","year":"2019","unstructured":"Sun H, Li S, Zheng X et al (2019) Remote sensing scene classification by gated bidirectional network. IEEE Trans Geosci Rem Sens PP(99):1\u201315","journal-title":"IEEE Trans Geosci Rem Sens"},{"key":"15519_CR52","unstructured":"Vaswani A, Shazeer N, Parmar N et al (2017) Attention is all you need[J]. Advances in Neural Information Processing Systems, 30"},{"issue":"1s","key":"15519_CR53","first-page":"1","volume":"17","author":"Y Wang","year":"2021","unstructured":"Wang Y (2021) Survey on deep multi-modal data analytics: collaboration, rivalry, and fusion. ACM Trans Multimed Comput Commun Appli (TOMM) 17 (1s):1\u201325","journal-title":"ACM Trans Multimed Comput Commun Appli (TOMM)"},{"key":"15519_CR54","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.neucom.2018.09.042","volume":"329","author":"D Wang","year":"2019","unstructured":"Wang D, Mao K (2019) Task-generic semantic convolutional neural network for web text-aided image classification. Neurocomputing 329:103\u2013115","journal-title":"Neurocomputing"},{"key":"15519_CR55","unstructured":"Wang Y, Zhang W, Wu L et al (2016) Iterative views agreement: an iterative low-rank based structured optimization method to multi-view spectral clustering. arXiv:1608.05560"},{"issue":"9","key":"15519_CR56","doi-asserted-by":"crossref","first-page":"4104","DOI":"10.1109\/JSTARS.2017.2705419","volume":"10","author":"G Wang","year":"2017","unstructured":"Wang G, Fan B, Xiang S et al (2017) Aggregating rich hierarchical features for scene classification in remote sensing imagery. IEEE J Selected Topics Appl Earth Observ Rem Sens 10(9):4104\u20134115","journal-title":"IEEE J Selected Topics Appl Earth Observ Rem Sens"},{"issue":"2","key":"15519_CR57","doi-asserted-by":"crossref","first-page":"1155","DOI":"10.1109\/TGRS.2018.2864987","volume":"57","author":"Q Wang","year":"2018","unstructured":"Wang Q, Liu S, Chanussot J et al (2018) Scene classification with recurrent attention of VHR remote sensing images. IEEE Trans Geosci Remote Sens 57(2):1155\u20131167","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"9","key":"15519_CR58","doi-asserted-by":"crossref","first-page":"7918","DOI":"10.1109\/TGRS.2020.3044655","volume":"59","author":"X Wang","year":"2021","unstructured":"Wang X, Wang S, Ning C et al (2021) Enhanced feature pyramid network with deep semantic embedding for remote sensing scene classification. IEEE Trans Geosci Rem Sens 59(9):7918\u20137932","journal-title":"IEEE Trans Geosci Rem Sens"},{"key":"15519_CR59","doi-asserted-by":"crossref","unstructured":"Wang W, Xie E, Li X et al (2021) Pyramid vision transformer: a versatile backbone for dense prediction without convolutions. International Conference on Computer Vision, 568\u2013578","DOI":"10.1109\/ICCV48922.2021.00061"},{"key":"15519_CR60","doi-asserted-by":"crossref","unstructured":"Woo S, Park J, Lee JY et al (2018) Cbam: convolutional block attention module. In: Proceedings of the European conference on computer vision (ECCV), pp 3\u201319","DOI":"10.1007\/978-3-030-01234-2_1"},{"issue":"8","key":"15519_CR61","first-page":"1489","volume":"33","author":"J Wu","year":"2010","unstructured":"Wu J, Rehg JM (2010) Centrist: a visual descriptor for scene categorization. IEEE Trans Pattern Anal Mach Intell 33(8):1489\u20131501","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"3","key":"15519_CR62","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1109\/TCYB.2018.2876591","volume":"50","author":"F Wu","year":"2018","unstructured":"Wu F, Jing XY, Dong X et al (2018) Intraspectrum discrimination and interspectrum correlation analysis deep network for multispectral face recognition. IEEE Trans Cybern 50(3):1009\u20131022","journal-title":"IEEE Trans Cybern"},{"key":"15519_CR63","doi-asserted-by":"crossref","first-page":"107632","DOI":"10.1016\/j.patcog.2020.107632","volume":"111","author":"F Wu","year":"2021","unstructured":"Wu F, Jing XY, Feng Y et al (2021) Spectrum-aware discriminative deep feature learning for multi-spectral face recognition. Pattern Recogn 111:107632","journal-title":"Pattern Recogn"},{"issue":"7","key":"15519_CR64","doi-asserted-by":"crossref","first-page":"3965","DOI":"10.1109\/TGRS.2017.2685945","volume":"55","author":"GS Xia","year":"2017","unstructured":"Xia GS, Hu J, Hu F (2017) AID: a benchmark data set for performance evaluation of aerial scene classification. IEEE Trans Geosci Remote Sens 55(7):3965\u20133981","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"10","key":"15519_CR65","doi-asserted-by":"crossref","first-page":"1072","DOI":"10.3390\/electronics8101072","volume":"8","author":"S Xia","year":"2019","unstructured":"Xia S, Zeng J, Leng L et al (2019) Ws-am: weakly supervised attention map for scene recognition. Electronics 8(10):1072","journal-title":"Electronics"},{"key":"15519_CR66","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.neucom.2019.09.066","volume":"373","author":"Z Xiong","year":"2020","unstructured":"Xiong Z, Yuan Y, Wang Q (2020) MSN: modality separation networks for RGB-D scene recognition. Neurocomputing 373:81\u201389","journal-title":"Neurocomputing"},{"key":"15519_CR67","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.ins.2020.06.011","volume":"539","author":"K Xu","year":"2020","unstructured":"Xu K, Huang H, Deng P et al (2020) Two-stream feature aggregation deep neural network for scene classification of remote sensing images[J]. Inform Sci 539:250\u2013268","journal-title":"Inform Sci"},{"key":"15519_CR68","doi-asserted-by":"crossref","unstructured":"Xu K, Huang H, Deng P (2021) Remote sensing image scene classification based on global-local dual-branch structure model. IEEE Geoscience and Remote Sensing Letters","DOI":"10.1109\/LGRS.2021.3075712"},{"key":"15519_CR69","doi-asserted-by":"crossref","unstructured":"Yang Y, Newsam S (2010) Bag-of-visual-words and spatial extensions for land-use classification. In: Proceedings of the 18th SIGSPATIAL international conference on advances in geographic information systems, pp 270\u2013279","DOI":"10.1145\/1869790.1869829"},{"issue":"5","key":"15519_CR70","doi-asserted-by":"crossref","first-page":"734","DOI":"10.3390\/rs10050734","volume":"10","author":"D Zeng","year":"2018","unstructured":"Zeng D, Chen S, Chen B et al (2018) Improving remote sensing scene classification by integrating global-context and local-object features. Remote Sens 10(5):734","journal-title":"Remote Sens"},{"issue":"3","key":"15519_CR71","doi-asserted-by":"crossref","first-page":"1793","DOI":"10.1109\/TGRS.2015.2488681","volume":"54","author":"F Zhang","year":"2015","unstructured":"Zhang F, Du B, Zhang L (2015) Scene classification via a gradient boosting random convolutional network framework. IEEE Trans Geosci Remote Sens 54(3):1793\u20131802","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"15519_CR72","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.ins.2016.10.019","volume":"376","author":"C Zhang","year":"2017","unstructured":"Zhang C, Zhu G, Huang Q et al (2017) Image classification by search with explicitly and implicitly semantic representations. Inform Sci 376:125\u2013135","journal-title":"Inform Sci"},{"issue":"5","key":"15519_CR73","doi-asserted-by":"crossref","first-page":"494","DOI":"10.3390\/rs11050494","volume":"11","author":"W Zhang","year":"2019","unstructured":"Zhang W, Tang P, Zhao L (2019) Remote sensing image scene classification using CNN-CapsNet. Remote Sens 11(5):494","journal-title":"Remote Sens"},{"key":"15519_CR74","doi-asserted-by":"crossref","unstructured":"Zhang J, Yang K, Constantinescu A et al (2021) Trans4Trans: efficient transformer for transparent object segmentation to help visually impaired people navigate in the real world. International Conference on Computer Vision, 1760\u20131770","DOI":"10.1109\/ICCVW54120.2021.00202"},{"issue":"2","key":"15519_CR75","first-page":"1","volume":"40","author":"C Zhang","year":"2021","unstructured":"Zhang C, Wang Y, Zhu L et al (2021) Multi-graph heterogeneous interaction fusion for social recommendation. ACM Trans Inform Syst (TOIS) 40 (2):1\u201326","journal-title":"ACM Trans Inform Syst (TOIS)"},{"key":"15519_CR76","first-page":"172","volume-title":"Learning hybrid part filters for scene recognition, European conference on computer vision","author":"Y Zheng","year":"2012","unstructured":"Zheng Y, Jiang YG, Xue X (2012) Learning hybrid part filters for scene recognition, European conference on computer vision. Springer, Berlin, pp 172\u2013185"},{"key":"15519_CR77","doi-asserted-by":"crossref","unstructured":"Zhou B, Khosla A, Lapedriza A et al (2016) Places: an image database for deep scene understanding, arXiv:1610.02055","DOI":"10.1167\/17.10.296"},{"issue":"4","key":"15519_CR78","doi-asserted-by":"crossref","first-page":"568","DOI":"10.3390\/rs10040568","volume":"10","author":"Q Zhu","year":"2018","unstructured":"Zhu Q, Zhong Y, Liu Y et al (2018) A deep-local-global feature fusion framework for high spatial resolution imagery scene classification. Remote Sens 10(4):568","journal-title":"Remote Sens"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-15519-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-15519-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-15519-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T07:19:50Z","timestamp":1704698390000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-15519-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,10]]},"references-count":78,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["15519"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-15519-2","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2023,6,10]]},"assertion":[{"value":"8 September 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 April 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 June 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}