{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T22:24:50Z","timestamp":1772490290216,"version":"3.50.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T00:00:00Z","timestamp":1601942400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T00:00:00Z","timestamp":1601942400000},"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":[[2021,2]]},"DOI":"10.1007\/s11042-020-09891-6","type":"journal-article","created":{"date-parts":[[2020,10,7]],"date-time":"2020-10-07T02:02:41Z","timestamp":1602036161000},"page":"5255-5272","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":62,"title":["G.V Black dental caries classification and preparation technique using optimal CNN-LSTM classifier"],"prefix":"10.1007","volume":"80","author":[{"given":"Prerna","family":"Singh","sequence":"first","affiliation":[]},{"given":"Priti","family":"Sehgal","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,6]]},"reference":[{"key":"9891_CR1","doi-asserted-by":"crossref","unstructured":"Aditi, Nagda MK, Poovammal E (2019) Image classification using a hybrid LSTM-CNN deep neural network. Int J Eng Adv Technol 8(6):1342\u20131348","DOI":"10.35940\/ijeat.F8602.088619"},{"key":"9891_CR2","unstructured":"Arul Selvan K (2011) A study on the antimicrobial effect of natural substances on clinical strains of streptococcus mutans. Ph.D. thesis"},{"key":"9891_CR3","doi-asserted-by":"crossref","unstructured":"Datta S, Chaki N (2015) Detection of dental caries lesion at early stage based on image analysis technique. IEEE International Conference on Computer Graphics. Vision and Information Security (CGVIS). IEEE, pp 89\u201393","DOI":"10.1109\/CGVIS.2015.7449899"},{"issue":"4","key":"9891_CR4","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1007\/s10618-019-00619-1","volume":"33","author":"HI Fawaz","year":"2019","unstructured":"Fawaz HI, Forestier G, Weber J, Idoumghar L, Muller PA (2019) Deep learning for time series classification:a review. Data Min Knowl Discov 33(4):917\u2013963","journal-title":"Data Min Knowl Discov"},{"key":"9891_CR5","doi-asserted-by":"crossref","unstructured":"Guo Y, Liu Y, Bakker EM, Guo Y, Lew MS (2018) CNN-RNN: a large-scale hierarchical image classification framework. Multimed Tools Appl 77:10251\u201310271","DOI":"10.1007\/s11042-017-5443-x"},{"key":"9891_CR6","doi-asserted-by":"crossref","unstructured":"Hwang J-J, Jung Y-H, Cho B-H (2019) An overview of deep learning in the field of dentistry. Imaging Sci Dent 49:2233\u20137822","DOI":"10.5624\/isd.2019.49.1.1"},{"key":"9891_CR7","doi-asserted-by":"crossref","unstructured":"Imangaliyev S, van der Veen MH, Volgenant CM, Keijser BJ, Crielaard W, Levin E (2016) Deep learning for classification of dental plaque images. In: Conca PP, Nicosia GG. Machine learning, optimization, and Big data. Second International Workshop, MOD 2016, Volterra, Italy, August 26\u201329, 2016, Revised Selected Papers. Springer, pp 407\u201310","DOI":"10.1007\/978-3-319-51469-7_34"},{"key":"9891_CR8","doi-asserted-by":"crossref","unstructured":"Ioannis E, Livieris E, Pintelas P Pintelas (2020) A CNN-LSTM model for gold price time-series forecasting. Neural Comput Appl. S.I: Emergingapplications of Deep Learning and Spiking ANN","DOI":"10.1007\/s00521-020-04867-x"},{"key":"9891_CR9","doi-asserted-by":"publisher","unstructured":"Karimian N, Salehi HS, Mahdian M, Alnajjar H, Tadinada A (2018) Deep learning classifier with optical coherence tomography images for early dental caries detection. Proc. SPIE 10473, Lasers in Dentistry XXIV, 1047304. https:\/\/doi.org\/10.1117\/12.2291088","DOI":"10.1117\/12.2291088"},{"key":"9891_CR10","doi-asserted-by":"publisher","unstructured":"Laurence J. Walsh (2018) Caries diagnosis aided by fluorescence. Dental caries diagnosis, prevention, and management. IntechOpen, Available from https:\/\/doi.org\/10.5772\/intechopen.75459","DOI":"10.5772\/intechopen.75459"},{"key":"9891_CR11","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.jdent.2018.07.015","volume":"77","author":"JH Lee","year":"2018","unstructured":"Lee JH, Kim DH, Jeong SN, Choi SH (2018) Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm. J Dent 77:106\u2013111","journal-title":"J Dent"},{"issue":"12","key":"9891_CR12","first-page":"1","volume":"18","author":"T Liu","year":"2012","unstructured":"Liu T, Bao J, Wang J, Zhang Y (2012) A hybrid CNN-LSTM Algorithm for online defect recognition of Co2Welding. Sensors 18(12):1\u201315","journal-title":"Sensors"},{"key":"9891_CR13","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.compbiomed.2016.11.003","volume":"80","author":"Y Miki","year":"2017","unstructured":"Miki Y, Muramatsu C, Hayashi T, Zhou X, Hara T, Katsumata A, Fujita H (2017) Classification of teeth in cone-beam CT using deep convolutional neural network. Comput Biol Med 80:24\u201329","journal-title":"Comput Biol Med"},{"issue":"4","key":"9891_CR14","doi-asserted-by":"publisher","first-page":"1053","DOI":"10.1007\/s00521-015-1920-1","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S (2016) Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Comput Appl 27(4):1053\u20131073","journal-title":"Neural Comput Appl"},{"key":"9891_CR15","doi-asserted-by":"crossref","unstructured":"Murata S, Lee C, Kawa CT, Date S (2017) Towards a fully automated diagnostic system for orthodontic treatment in dentistry. IEEE 13th International Conference on e-Science, pp 1\u20138","DOI":"10.1109\/eScience.2017.12"},{"key":"9891_CR16","doi-asserted-by":"publisher","first-page":"15481","DOI":"10.1007\/s11042-019-7525-4","volume":"79","author":"G Murtaza","year":"2019","unstructured":"Murtaza G, Shuib L, Mujtaba G, Mujtaba G, Raza G (2019) Breast cancer multi-classification through deep neural network and hierarchical classification approach. Multimedia Tools Appl 79:15481\u201315511","journal-title":"Multimedia Tools Appl"},{"key":"9891_CR17","doi-asserted-by":"crossref","unstructured":"Naebi M, Saberi E, Fakour SR, Naebi A, Tabatabaei SH, Moghadam SA, Bozorgmehr E, Behnam ND, Azimi H (2016) Detection of carious lesions and restorations using particle swarm optimization algorithm. Int J Dent 2016","DOI":"10.1155\/2016\/3264545"},{"key":"9891_CR18","doi-asserted-by":"crossref","unstructured":"Prajapati SA, Nagaraj R, Mitra S (2017) Classification of dental diseases using CNN and transfer learning. 5th International Symposium on Computational and Business Intelligence (ISCBI). IEEE, pp 70\u201374","DOI":"10.1109\/ISCBI.2017.8053547"},{"key":"9891_CR19","doi-asserted-by":"crossref","unstructured":"Rahman CM, Rashid TM (2019) Dragonfly Algorithm and its applications in applied science survey. Comput Intell Neurosci 2019, Article ID 9293617","DOI":"10.1155\/2019\/9293617"},{"key":"9891_CR20","doi-asserted-by":"crossref","unstructured":"Salehi HS, Mahdian M, Murshid MM, Judex S, Tadinada A (2019) Deep learning-based quantitative analysis of dental caries using optical coherence tomography: an ex vivo study. In: Lasers in Dentistry XXV, vol 10857, Proceeding International Society for Optics and Photonics","DOI":"10.1117\/12.2510076"},{"key":"9891_CR21","unstructured":"Scheid RC, Weiss G (2007) Dental anatomy Williams & Wilkins, 8th edn"},{"key":"9891_CR22","doi-asserted-by":"crossref","unstructured":"Singh P, Sehgal P (2017) Automated caries detection based on Radon transformation and DCT. 8th International Conference on Computing Communication and Technologies N (ICCCNT).IEEE, pp 1\u20136","DOI":"10.1109\/ICCCNT.2017.8204030"},{"key":"9891_CR23","doi-asserted-by":"crossref","unstructured":"Singh P, Sehgal P (2019) G.V Black Classification of dental caries using CNN. Accepted in 4th International Conference on Advanced Computing and Intelligent Engineering (ICACIE)","DOI":"10.1007\/978-981-15-6584-7_11"},{"key":"9891_CR24","unstructured":"Srivastava MM, Kumar P, Pradhan L, Varadarajan SK (2017) Detection of tooth caries in bitewing radiograph using deep learning. NIPS 2017 Workshop on Machine Learning for health"},{"key":"9891_CR25","doi-asserted-by":"crossref","unstructured":"Yadav AK, Roy R, Kumar CS, Kumar R, Kumar AP (2015) Algorithm for de-noising of color images based on median filter. Third International Conference on Image Information Processing (ICIIP). IEEE, pp 428\u2013432","DOI":"10.1109\/ICIIP.2015.7414811"},{"key":"9891_CR26","unstructured":"Youlian Z, Cheng H, Lifang Z (2013) A median image filtering algorithm based on statistical histogram. Fifth International Conference on Measuring Technology and Mechatronics Automation. IEEE, pp 17\u201320"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09891-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-09891-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09891-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,6]],"date-time":"2021-10-06T07:16:49Z","timestamp":1633504609000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-09891-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,6]]},"references-count":26,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["9891"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09891-6","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,6]]},"assertion":[{"value":"28 February 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 August 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 September 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 October 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}