{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T22:23:00Z","timestamp":1776205380670,"version":"3.50.1"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"29","license":[{"start":{"date-parts":[[2022,8,24]],"date-time":"2022-08-24T00:00:00Z","timestamp":1661299200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,8,24]],"date-time":"2022-08-24T00:00:00Z","timestamp":1661299200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2022,12]]},"DOI":"10.1007\/s11042-022-13490-y","type":"journal-article","created":{"date-parts":[[2022,8,24]],"date-time":"2022-08-24T07:10:28Z","timestamp":1661325028000},"page":"42413-42431","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Real-time monitoring system of cyanobacteria blooms using deep learning approach"],"prefix":"10.1007","volume":"81","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9323-8621","authenticated-orcid":false,"given":"LiFang","family":"Chen","sequence":"first","affiliation":[]},{"given":"Yu","family":"Shi","sequence":"additional","affiliation":[]},{"given":"YuanXin","family":"Du","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,8,24]]},"reference":[{"key":"13490_CR1","doi-asserted-by":"publisher","unstructured":"Chen LC, Papandreou G, Kokkinos I et al (2014) Semantic image segmentation with deep convolutional nets and fully connected CRFs. Comput Sci (4):357\u2013361. https:\/\/doi.org\/10.48550\/arXiv.1606.00915","DOI":"10.48550\/arXiv.1606.00915"},{"issue":"04","key":"13490_CR2","first-page":"606","volume":"50","author":"LQ Chen","year":"2016","unstructured":"Chen LQ, Zhang J, Chen XL et al (2016) Research on meteorological factors and Logistic prediction model of cyanobacterical blooms in Erhai Lake. J Cent China Norm Univ (Nat Sci) 50(04):606\u2013611","journal-title":"J Cent China Norm Univ (Nat Sci)"},{"issue":"4","key":"13490_CR3","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","volume":"40","author":"LC Chen","year":"2018","unstructured":"Chen LC, Papandreou G, Kokkinos I et al (2018) DeepLab: Semantic image segmentation with deep convolutional nets, Atrous convolution, and fully connected CRFs. IEEE Trans Pattern Anal Mach Intell 40(4):834\u2013848","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"04","key":"13490_CR4","first-page":"97","volume":"38","author":"SZ Fang","year":"2019","unstructured":"Fang SZ, Yan X, Peng B (2019) Design and implementation of the cyanobacteria algal bloom monitoring and pre-warning spatial information system in Lake Dian. Inform Technol Netw Secur 38(04):97\u2013101","journal-title":"Inform Technol Netw Secur"},{"key":"13490_CR5","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M et al (2014) Generative adversarial nets. Proceedings of the 2014 International Conference on Neural Information Processing Systems. MIT Press, Cambridge, 2672 -2680"},{"issue":"7","key":"13490_CR6","first-page":"2255","volume":"35","author":"JM Jia","year":"2015","unstructured":"Jia JM, Luo w, Du TT et al (2015) Valuation of changes of ecosystem services of Tai Lake in recent 10 years. Acta Ecol Sin 35(7):2255\u20132264","journal-title":"Acta Ecol Sin"},{"key":"13490_CR7","unstructured":"Klinger R, Tomanek K (2007) Classical probabilistic models and conditional random fields.\u00a0[online] Available:\u00a0http:\/\/ls11-www.cs.uni-dortmund.de\/_media\/techreports\/tr07-13.pdf"},{"key":"13490_CR8","unstructured":"Kingma D, Ba J (2014) Adam: A method for stochastic optimization. arXiv preprint arXiv: 1412.6980"},{"issue":"6","key":"13490_CR9","doi-asserted-by":"publisher","first-page":"1256","DOI":"10.18307\/2016.0611","volume":"28","author":"YC Li","year":"2016","unstructured":"Li YC, Xie XP, Zhu XL et al (2016) Applying remote sensing techniques in analysis of temperature features causing cyanobacteria bloom in Lake Taihu. J Lake Sci 28(6):1256\u20131264","journal-title":"J Lake Sci"},{"issue":"4","key":"13490_CR10","first-page":"153","volume":"40","author":"X Li","year":"2017","unstructured":"Li X, Sun W, Li L (2017) Study on the recognition of spirulina based on visible light remote sensing of the small UAV. Geo Spat Inf Technol 40(4):153\u2013158","journal-title":"Geo Spat Inf Technol"},{"issue":"8","key":"13490_CR11","first-page":"1247","volume":"39","author":"Y Lin","year":"2011","unstructured":"Lin Y, Pan C, Chen YY et al (2011) Recognition of cyanobacteria bloom based on spectral analysis of remote sensing imagery. J Tongji Univ (Nat Sci) 39(8):1247\u20131252","journal-title":"J Tongji Univ (Nat Sci)"},{"issue":"09","key":"13490_CR12","first-page":"66","volume":"31","author":"JP Liu","year":"2015","unstructured":"Liu JP, Ma XY (2015) Forecast of algae content in raw water of waterworks based on GIS and RBF neural network. China Water Wastewater 31(09):66\u201369","journal-title":"China Water Wastewater"},{"key":"13490_CR13","doi-asserted-by":"publisher","first-page":"4527","DOI":"10.1007\/s11042-018-6058-6","volume":"78","author":"F Liu","year":"2019","unstructured":"Liu F, Chen Z, Wang J (2019) Video image target monitoring based on RNN-LSTM. Multimed Tools Appl 78:4527\u20134544","journal-title":"Multimed Tools Appl"},{"key":"13490_CR14","doi-asserted-by":"crossref","unstructured":"Long J, Shelhamer E, Darrell T (2015) Fully convolutional networks for semantic segmentation. 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","DOI":"10.1109\/CVPR.2015.7298965"},{"issue":"4","key":"13490_CR15","first-page":"254","volume":"35","author":"AN Luo","year":"2018","unstructured":"Luo AN, Zheng J (2018) Semantic segmentation of cyanobacteria pictures based on DCNN under complicated illumination. Comput Appl Softw 35(4):254\u2013259","journal-title":"Comput Appl Softw"},{"key":"13490_CR16","doi-asserted-by":"publisher","unstructured":"Perdig\u00e3o P, Lous\u00e3 P, Ascenso J et al (2020) Visual monitoring of High-Sea fishing activities using deep learning-based image processing. Multimed Tools Appl. https:\/\/doi.org\/10.1007\/s11042-020-08949-9","DOI":"10.1007\/s11042-020-08949-9"},{"issue":"2","key":"13490_CR17","doi-asserted-by":"publisher","first-page":"53","DOI":"10.12677\/IJE.2018.72008","volume":"7","author":"J Xia","year":"2018","unstructured":"Xia J, Wu WQ, Xu HY (2018) Application of BP neural network based on principal component analysis in algal bloom prediction. Int J Ecol 7(2):53\u201360","journal-title":"Int J Ecol"},{"issue":"7","key":"13490_CR18","first-page":"2119","volume":"38","author":"JB Yu","year":"2018","unstructured":"Yu JB, Shang FF, Wang XY (2018) Cyanobacterial bloom forecast method based on genetic algorithm-first order lag filter and long short-term memory network. J Comput Appl 38(7):2119\u20132123","journal-title":"J Comput Appl"},{"key":"13490_CR19","doi-asserted-by":"crossref","unstructured":"Zhu YD, Wang Y, Cheng LG et al (2014) Application of cyanobacteria blooms integrated monitoring system in Taihu Lake. Water Resour Informatization (01):33\u201338","DOI":"10.1007\/s00343-015-4019-8"},{"key":"13490_CR20","unstructured":"Zhu PIsolaJun-Yan, Zhou et al (2018) Image-to-image translation with conditional adversarial networks. arXiv preprint arXiv: 1611.07004v3 [cs.CV]"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13490-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-13490-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13490-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,26]],"date-time":"2022-11-26T22:53:58Z","timestamp":1669503238000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-13490-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,24]]},"references-count":20,"journal-issue":{"issue":"29","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["13490"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-13490-y","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,24]]},"assertion":[{"value":"9 December 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 August 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 July 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 August 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}