{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T04:38:59Z","timestamp":1754109539499},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T00:00:00Z","timestamp":1659571200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T00:00:00Z","timestamp":1659571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Beijing Natural Science Foundation","award":["4212025"],"award-info":[{"award-number":["4212025"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61876018"],"award-info":[{"award-number":["61876018"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976017"],"award-info":[{"award-number":["61976017"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s10489-022-03697-9","type":"journal-article","created":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T11:06:03Z","timestamp":1659611163000},"page":"8959-8977","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Minimum volume simplex-based scene representation and attribute recognition with feature fusion"],"prefix":"10.1007","volume":"53","author":[{"given":"Zhiyuan","family":"Zou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weibin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiwei","family":"Xing","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shunli","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,8,4]]},"reference":[{"key":"3697_CR1","doi-asserted-by":"crossref","unstructured":"Yin G, Sheng L, Liu B, Yu N, Wang X, Shao J (2019) Context and attribute grounded dense captioning. In: 2019 IEEE Conference on computer vision and pattern recognition, CVPR 2019, 15\u201320","DOI":"10.1109\/CVPR.2019.00640"},{"key":"3697_CR2","doi-asserted-by":"crossref","unstructured":"Choi S, Kim JT, Choo J (2019) Cars Can\u2019t Fly up in the sky: Improving Urban-Scene Segmentation via Height-driven Attention Networks. In: 2019 IEEE Conference on computer vision and pattern recognition, CVPR 2019, 15\u201320","DOI":"10.1109\/CVPR42600.2020.00939"},{"issue":"3","key":"3697_CR3","doi-asserted-by":"publisher","first-page":"596","DOI":"10.1109\/TPAMI.2018.2799846","volume":"41","author":"R Zhang","year":"2019","unstructured":"Zhang R, Lin L, Wang G, Wang M, Zuo W (2019) Hierarchical scene parsing by weakly supervised learning with image descriptions. IEEE Trans Pattern Anal Mach Intell 41(3):596\u2013610","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3697_CR4","doi-asserted-by":"crossref","unstructured":"Sulistiyo AMD, Kawanishi Y, Deguchi D, Hirayama T, Ide I, Zheng JY, Murase H (2018) Attribute-aware Semantic Segmentation of Road Scenes for Understanding Pedestrian Orientations. In: IEEE 21st international conference on intelligent transportation systems, ITSC","DOI":"10.1109\/ITSC.2018.8569372"},{"key":"3697_CR5","doi-asserted-by":"publisher","first-page":"106777","DOI":"10.1016\/j.knosys.2021.106777","volume":"215","author":"GB Vitor","year":"2021","unstructured":"Vitor GB, Victorino AC, Ferreira JV (2021) Modeling evidential grids using semantic context information for dynamic scene perception. Knowledge-Based Systems 215:106777","journal-title":"Knowledge-Based Systems"},{"key":"3697_CR6","doi-asserted-by":"publisher","first-page":"107205","DOI":"10.1016\/j.patcog.2020.107205","volume":"102","author":"L Xie","year":"2020","unstructured":"Xie L, Lee F, Liu L, Kotanic K, Chen Q (2020) Scene recognition: A comprehensive survey. Pattern Recognit 102:107205","journal-title":"Pattern Recognit"},{"issue":"6","key":"3697_CR7","doi-asserted-by":"publisher","first-page":"1519","DOI":"10.1109\/TMM.2019.2944241","volume":"22","author":"H Zeng","year":"2020","unstructured":"Zeng H, Song X, Chen G (2020) Learning scene attribute for scene recognition. IEEE IEEE Trans Multimed 22(6):1519\u2013 1530","journal-title":"IEEE IEEE Trans Multimed"},{"issue":"3","key":"3697_CR8","doi-asserted-by":"publisher","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. IJCV 42(3):145\u2013175","journal-title":"IJCV"},{"key":"3697_CR9","doi-asserted-by":"crossref","unstructured":"Lazebnik S, Schmid C, Ponce J (2006) Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In: 2006 IEEE Conference on computer vision and pattern recognition, CVPR 2006, 17\u201322","DOI":"10.1109\/CVPR.2006.68"},{"key":"3697_CR10","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1007\/s11263-013-0695-z","volume":"108","author":"G Patterson","year":"2014","unstructured":"Patterson G, Xu C, Su H, Hays J (2014) The SUN attribute database: beyond categories for deeper scene understanding. Int J Comput Vis 108:59\u201381","journal-title":"Int J Comput Vis"},{"key":"3697_CR11","unstructured":"Elisseeff A, Weston J (2001) A kernel method for multi-labelled classification. In: Proceedings of the 14th international conference on neural information processing systems: natural and synthetic, in: NIPS\u201901, MIT Press, pp 681\u2013687"},{"issue":"7","key":"3697_CR12","doi-asserted-by":"publisher","first-page":"2038","DOI":"10.1016\/j.patcog.2006.12.019","volume":"40","author":"M-L Zhang","year":"2007","unstructured":"Zhang M-L, Zhou Z-H (2007) Ml-knn: a lazy learning approach to multi-label learning. Pattern Recogn 40(7):2038\u20132048","journal-title":"Pattern Recogn"},{"issue":"10","key":"3697_CR13","doi-asserted-by":"publisher","first-page":"4883","DOI":"10.1109\/TIP.2019.2913079","volume":"28","author":"L Chen","year":"2019","unstructured":"Chen L, Zhan W, Tian W, He Y, Zou Q (2019) Deep integration: a Multi-Label architecture for road scene recognition. IEEE Trans Image Process 28(10):4883\u20134898","journal-title":"IEEE Trans Image Process"},{"issue":"12","key":"3697_CR14","doi-asserted-by":"publisher","first-page":"6025","DOI":"10.1109\/TIP.2018.2864920","volume":"27","author":"L Song","year":"2018","unstructured":"Song L, Liu J, Qian B, Sun M, Yang K, Sun M, Abbas S (2018) A deep multi-modal CNN for multi-instance multi-label image classification. IEEE Trans Image Process 27(12):6025\u20136038","journal-title":"IEEE Trans Image Process"},{"key":"3697_CR15","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.neucom.2019.05.024","volume":"357","author":"N Khan","year":"2019","unstructured":"Khan N, Chaudhuri U, Banerjee B, Chaudhuri S (2019) Graph convolutional network for multi-label VHR remote sensing scene recognition. Neurocomputing 357:36\u201346","journal-title":"Neurocomputing"},{"issue":"12","key":"3697_CR16","doi-asserted-by":"publisher","first-page":"2478","DOI":"10.1109\/TPAMI.2015.2424880","volume":"37","author":"S Wang","year":"2015","unstructured":"Wang S, Wnag Y, Zhu SC (2015) Learning hierarchical space tiling for scene modeling, parsing and attribute tagging. IEEE Trans Pattern Anal Mach Intell 37(12):2478\u20132491","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3697_CR17","unstructured":"Dalal N, Triggs B (2005) Histogram of oriented gradient object detection. In: 2005 IEEE Conference on computer vision and pattern recognition, CVPR"},{"issue":"3","key":"3697_CR18","doi-asserted-by":"publisher","first-page":"2007","DOI":"10.1145\/1276377.1276381","volume":"26","author":"J-F Lalonde","year":"2007","unstructured":"Lalonde J-F, Hoiem D, Efros AA, Rother C, Winn J, Criminisi A (2007) Photo clip art. ACM Transactions on Graphics 26(3):2007","journal-title":"ACM Transactions on Graphics"},{"key":"3697_CR19","doi-asserted-by":"crossref","unstructured":"Shechtman E, Irani M (2007) Matching local self-similarities across images and videos. In: 2007 IEEE Conference on computer vision and pattern recognition, CVPR","DOI":"10.1109\/CVPR.2007.383198"},{"issue":"1","key":"3697_CR20","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1109\/TIP.2015.2498407","volume":"25","author":"J Zhu","year":"2016","unstructured":"Zhu J, Wu T, Zhu S-C, Yang X, Zhang W (2016) A reconfigurable tangram model for scene representation and categorization. IEEE Trans Image Process 25(1):150\u2013166","journal-title":"IEEE Trans Image Process"},{"key":"3697_CR21","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.cviu.2015.05.012","volume":"138","author":"F Tung","year":"2015","unstructured":"Tung F, Little JJ (2015) Improving scene attribute recognition using web-scale object detectors. Comput Vis Image Underst 138:86\u201391","journal-title":"Comput Vis Image Underst"},{"key":"3697_CR22","doi-asserted-by":"crossref","unstructured":"Chen X, Shrivastava A, Gupta A (2013) NEIL: Extracting visual knowledge from web data. In: IEEE International conference on computer vision","DOI":"10.1109\/ICCV.2013.178"},{"key":"3697_CR23","doi-asserted-by":"crossref","unstructured":"Chatfield K, Simonyan K, Vedaldi A, Zisserman A (2014) Return of the devil in the details: delving deep into convolutional nets. In: 2014 British machine vision conference","DOI":"10.5244\/C.28.6"},{"key":"3697_CR24","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R, Li L, Li K, Fei-Fei L (2009) Imagenet: A large-scale hierarchical image database. In: 2009 IEEE Conference on computer vision and pattern recognition, CVPR","DOI":"10.1109\/CVPR.2009.5206848"},{"issue":"4","key":"3697_CR25","doi-asserted-by":"publisher","first-page":"2055","DOI":"10.1109\/TIP.2017.2675339","volume":"26","author":"L Wang","year":"2017","unstructured":"Wang L, Guo S, Huang W, Xiong Y, Qiao Y (2017) Knowledge guided disambiguation for large-scale scene classification with multi-resolution CNNs. IEEE Trans Image Process 26(4):2055\u20132068","journal-title":"IEEE Trans Image Process"},{"key":"3697_CR26","doi-asserted-by":"crossref","unstructured":"Qi K, Yang C, Shen S (2021) A multi-level improved circle pooling for scene classification of high-resolution remote sensing imagery. Neurocomputing","DOI":"10.1016\/j.neucom.2021.08.022"},{"key":"3697_CR27","doi-asserted-by":"crossref","unstructured":"Yuan X, Qiao Z, Meyarian A (2021) Scale attentive network for scene recognition. Neurocomputing","DOI":"10.1016\/j.neucom.2021.12.053"},{"key":"3697_CR28","doi-asserted-by":"crossref","unstructured":"Lin C, Lee F, Chen Q (2022) Scene recognition using multiple representation network. Applied Soft Computing","DOI":"10.1016\/j.asoc.2022.108530"},{"key":"3697_CR29","doi-asserted-by":"crossref","unstructured":"Zou Z, Liu W, Xing W (2021) AdaNFF: A new method for adaptive nonnegative multi-feature fusion to scene classification. Pattern Recognit","DOI":"10.1016\/j.patcog.2021.108402"},{"issue":"4","key":"3697_CR30","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1109\/TGRS.2005.844293","volume":"43","author":"JMP Nascimento","year":"2005","unstructured":"Nascimento JMP, Bioucas-Dias JM (2005) Vertex component analysis: a fast algorithm to unmix hyperspectral data. IEEE Trans Geosci Remote Sens 43(4):898\u2013910","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"9","key":"3697_CR31","doi-asserted-by":"publisher","first-page":"5067","DOI":"10.1109\/TGRS.2015.2417162","volume":"53","author":"J Li","year":"2015","unstructured":"Li J, Agathos A, Zaharie D, Bioucas-Dias JM, Plaza A, Li X (2015) Minimum volume simplex analysis: a fast algorithm for linear hyperspectral unmixing. IEEE Trans Geosci Remote Sens 53(9):5067\u20135082","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"8","key":"3697_CR32","doi-asserted-by":"publisher","first-page":"1946","DOI":"10.1109\/TSP.2015.2508778","volume":"64","author":"C-H Lin","year":"2016","unstructured":"Lin C-H, Chi C-Y, Wang Y-H, Chan T-H (2016) A fast hyperplane-based minimum-volume enclosing simplex algorithm for blind hyper-spectral unmixing. IEEE Transactions on Signal Processing 64(8):1946\u2013196","journal-title":"IEEE Transactions on Signal Processing"},{"issue":"11","key":"3697_CR33","doi-asserted-by":"publisher","first-page":"6431","DOI":"10.1109\/TGRS.2017.2728104","volume":"55","author":"S Zhang","year":"2017","unstructured":"Zhang S, Agathos A, Li J (2017) Robust minimum volume simplex analysis for hyperspectral unmixing. IEEE Trans Geosci Remote Sens 55(11):6431\u20136439","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"23","key":"3697_CR34","doi-asserted-by":"publisher","first-page":"6254","DOI":"10.1109\/TSP.2016.2602800","volume":"64","author":"X Fu","year":"2016","unstructured":"Fu X, Huang K, Yang B, Ma W-K, Ni D (2016) sidiropoulos, Robust volume minimization-based matrix factorization for remote sensing and document clustering. IEEE Trans Signal Process 64(23):6254\u20136268","journal-title":"IEEE Trans Signal Process"},{"key":"3697_CR35","doi-asserted-by":"crossref","unstructured":"Leplat V, Ang AMS, Gillis N (2019) Minimum-volume rank-deficient nonnegative matrix factorizations. ICASSP, pp 3402\u20133406","DOI":"10.1109\/ICASSP.2019.8682280"},{"key":"3697_CR36","unstructured":"Marrinan T, Gillis N (2020) Hyperspectral unmixing with rare endmembers via minimax nonnegative matrix factorization. EUSIPCO, pp 1015\u20131019"},{"issue":"9","key":"3697_CR37","doi-asserted-by":"publisher","first-page":"6633","DOI":"10.1109\/TGRS.2019.2907567","volume":"57","author":"X Wang","year":"2019","unstructured":"Wang X, Zhong Y, Zhang L, Xu Y (2019) Blind hyperspectral unmixing considering the adjacency effect. IEEE Trans Geosci Remote Sens 57(9):6633\u20136649","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"4","key":"3697_CR38","doi-asserted-by":"publisher","first-page":"293","DOI":"10.4103\/0256-4602.64604","volume":"27","author":"UG Mangai","year":"2010","unstructured":"Mangai UG, Samanta S, Das S, Roy PC (2010) A survey of decision fusion and feature fusion strategies for pattern classification. IETE Tech Rev 27(4):293\u2013307","journal-title":"IETE Tech Rev"},{"key":"3697_CR39","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.inffus.2017.12.007","volume":"44","author":"D Charte","year":"2018","unstructured":"Charte D, Charte F, Garcia S, del Jesus MJ, Herrera F (2018) A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines. Information Fusion 44:78\u201396","journal-title":"Information Fusion"},{"issue":"5","key":"3697_CR40","doi-asserted-by":"publisher","first-page":"1135","DOI":"10.1109\/TPAMI.2012.198","volume":"35","author":"AJ Ma","year":"2013","unstructured":"Ma AJ, Yuen PC, Lai JH (2013) Linear dependency modeling for classifier fusion and feature combination. IEEE Trans Pattern Anal Mach Intell 35(5):1135\u20131148","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3697_CR41","unstructured":"Baggenstoss PM (2016) Maximum entropy feature fusion. In: International conference on information fusion, pp 1163\u20131169"},{"key":"3697_CR42","doi-asserted-by":"publisher","first-page":"104794","DOI":"10.1016\/j.knosys.2019.06.002","volume":"182","author":"Y Liu","year":"2019","unstructured":"Liu Y, Tang A, Cai F, Ren P, Sun Z (2019) Multi-feature based Question\u2013Answerer Model Matching for predicting response time in CQA. Knowledge-Based Systems 182:104794","journal-title":"Knowledge-Based Systems"},{"issue":"1","key":"3697_CR43","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1109\/TPAMI.2013.109","volume":"36","author":"S Shekhar","year":"2014","unstructured":"Shekhar S, Patel VM, Nasrabadi NM, Chellapa R (2014) Joint sparse representation for robust multimodal biometrics recognition. IEEE Trans Pattern Anal Mach Intell 36(1):113\u2013126","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"11","key":"3697_CR44","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta R, Shaji A, Smith K, Lucchi A, Fua P, Susstrunk S (2012) SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274\u20132281","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"10","key":"3697_CR45","doi-asserted-by":"publisher","first-page":"2756","DOI":"10.1162\/neco.2007.19.10.2756","volume":"19","author":"CJ Lin","year":"2007","unstructured":"Lin CJ (2007) Projected gradient methods for non-negative matrix factorization. Neural Comput 19(10):2756\u20132779","journal-title":"Neural Comput"},{"key":"3697_CR46","doi-asserted-by":"crossref","unstructured":"Quattoni A, Torralba A (2009) Recognizing indoor scenes. In: 2009 IEEE Conference on computer vision and pattern recognition, CVPR","DOI":"10.1109\/CVPR.2009.5206537"},{"key":"3697_CR47","doi-asserted-by":"crossref","unstructured":"Zhou B, Lapedriza A, Khosla A, Oliva A, Torralba A (2017) Places: A 10 million Image Database for Scene Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence","DOI":"10.1167\/17.10.296"},{"issue":"5","key":"3697_CR48","doi-asserted-by":"publisher","first-page":"1182","DOI":"10.1109\/TMM.2019.2942478","volume":"22","author":"L Xie","year":"2020","unstructured":"Xie L, Lee F, Liu L (2020) Hierarchical coding of convolutional features for scene recognition. IEEE Transactions on Multimedia 22(5):1182\u20131192","journal-title":"IEEE Transactions on Multimedia"},{"key":"3697_CR49","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1016\/j.patcog.2017.09.025","volume":"74","author":"X Chenga","year":"2018","unstructured":"Chenga X, Lub J, Fengb J, Yuan B, Zhou J (2018) Scene recognition with objectness. Pattern Recogn 74:474\u2013487","journal-title":"Pattern Recogn"},{"key":"3697_CR50","doi-asserted-by":"crossref","unstructured":"Liu Y, Chen Q, Chen W, Wassell I (2018) Dictionary learning inspired deep network for scene recognition. In: Proceedings of AAAI conference on artificial intelligence, pp 7178\u20137185","DOI":"10.1609\/aaai.v32i1.12312"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03697-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-022-03697-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03697-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,30]],"date-time":"2023-04-30T09:17:45Z","timestamp":1682846265000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-022-03697-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,4]]},"references-count":50,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["3697"],"URL":"https:\/\/doi.org\/10.1007\/s10489-022-03697-9","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,4]]},"assertion":[{"value":"29 April 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 August 2022","order":2,"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 that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}