{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T12:07:52Z","timestamp":1649160472492},"reference-count":19,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2020,2,27]],"date-time":"2020-02-27T00:00:00Z","timestamp":1582761600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,2,27]],"date-time":"2020-02-27T00:00:00Z","timestamp":1582761600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1007\/s00521-020-04785-y","type":"journal-article","created":{"date-parts":[[2020,2,27]],"date-time":"2020-02-27T14:02:51Z","timestamp":1582812171000},"page":"1811-1812","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Special issue on deep learning and neural computing for intelligent sensing and control"],"prefix":"10.1007","volume":"32","author":[{"given":"Xiaomeng","family":"Ma","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingyuan","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,2,27]]},"reference":[{"key":"4785_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-04739-4","author":"P Wei","year":"2020","unstructured":"Wei P, He F, Zou Y (2020) Content semantic image analysis and storage method based on intelligent computing of machine learning annotation. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-020-04739-4","journal-title":"Neural Comput Appl"},{"key":"4785_CR2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04621-y","author":"X Zhong","year":"2019","unstructured":"Zhong X, Liu J, Li L et al (2019) An emotion classification algorithm based on SPT-CapsNet. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04621-y","journal-title":"Neural Comput Appl"},{"key":"4785_CR3","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04620-z","author":"DK Jain","year":"2019","unstructured":"Jain DK, Jain R, Upadhyay Y et al (2019) Deep refinement: capsule network with attention mechanism-based system for text classification. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04620-z","journal-title":"Neural Comput Appl"},{"key":"4785_CR4","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04571-5","author":"K Guo","year":"2019","unstructured":"Guo K, Yang M, Zhu H (2019) Application research of improved genetic algorithm based on machine learning in production scheduling. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04571-5","journal-title":"Neural Comput Appl"},{"key":"4785_CR5","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04567-1","author":"Y Zheng","year":"2019","unstructured":"Zheng Y, Song Q, Liu J et al (2019) Research on motion pattern recognition of exoskeleton robot based on multimodal machine learning model. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04567-1","journal-title":"Neural Comput Appl"},{"key":"4785_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04492-3","author":"K Gu","year":"2019","unstructured":"Gu K, Zhou Y, Sun H et al (2019) Prediction of air quality in Shenzhen based on neural network algorithm. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04492-3","journal-title":"Neural Comput Appl"},{"key":"4785_CR7","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04505-1","author":"Y Zhang","year":"2019","unstructured":"Zhang Y, Lian J, Rong L et al (2019) Even faster retinal vessel segmentation via accelerated singular value decomposition. Neural Comput & Applic. https:\/\/doi.org\/10.1007\/s00521-019-04505-1","journal-title":"Neural Comput & Applic"},{"key":"4785_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04493-2","author":"Y Zhu","year":"2019","unstructured":"Zhu Y, Zheng Y (2019) Traffic identification and traffic analysis based on support vector machine. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04493-2","journal-title":"Neural Comput Appl"},{"key":"4785_CR9","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04501-5","author":"Z Shi","year":"2019","unstructured":"Shi Z, Feng Y, Zhao M et al (2019) A joint deep neural networks-based method for single nighttime rainy image enhancement. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04501-5","journal-title":"Neural Comput Appl"},{"key":"4785_CR10","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04495-0","author":"Z Fan","year":"2019","unstructured":"Fan Z, Xu F, Qi X et al (2019) Classification of Alzheimer\u2019s disease based on brain MRI and machine learning. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04495-0","journal-title":"Neural Comput Appl"},{"key":"4785_CR11","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04496-z","author":"Z Zhong","year":"2019","unstructured":"Zhong Z, Li H (2019) Recognition and prediction of ground vibration signal based on machine learning algorithm. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04496-z","journal-title":"Neural Comput Appl"},{"key":"4785_CR12","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04491-4","author":"L Zhang","year":"2019","unstructured":"Zhang L, Sheng Z, Li Y et al (2019) Image object detection and semantic segmentation based on convolutional neural network. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04491-4","journal-title":"Neural Comput Appl"},{"key":"4785_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04494-1","author":"P Li","year":"2019","unstructured":"Li P (2019) Research on radar signal recognition based on automatic machine learning. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04494-1","journal-title":"Neural Comput Appl"},{"key":"4785_CR14","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04378-4","author":"S Li","year":"2019","unstructured":"Li S, Zhang X (2019) Research on orthopedic auxiliary classification and prediction model based on XGBoost algorithm. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04378-4","journal-title":"Neural Comput Appl"},{"key":"4785_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04379-3","author":"M Du","year":"2019","unstructured":"Du M, Luo J, Wang S et al (2019) Genetic algorithm combined with BP neural network in hospital drug inventory management system. Neural Comput & Appl. https:\/\/doi.org\/10.1007\/s00521-019-04379-3","journal-title":"Neural Comput & Appl"},{"key":"4785_CR16","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04376-6","author":"Y Yuan","year":"2019","unstructured":"Yuan Y, Tian Z, Wang C et al (2019) A Q-learning-based approach for virtual network embedding in data center. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04376-6","journal-title":"Neural Comput Appl"},{"key":"4785_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04340-4","author":"Y Ren","year":"2019","unstructured":"Ren Y, Wang C, Li B et al (2019) A genetic algorithm for fuzzy random and low-carbon integrated forward\/reverse logistics network design. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04340-4","journal-title":"Neural Comput Appl"},{"key":"4785_CR18","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04339-x","author":"H Xu","year":"2019","unstructured":"Xu H, Jiang C (2019) Deep belief network-based support vector regression method for traffic flow forecasting. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04339-x","journal-title":"Neural Comput Appl"},{"key":"4785_CR19","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04341-3","author":"S Li","year":"2019","unstructured":"Li S, Chen J, Xiang J (2019) Applications of deep convolutional neural networks in prospecting prediction based on two-dimensional geological big data. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-019-04341-3","journal-title":"Neural Comput Appl"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-04785-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-020-04785-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-04785-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,26]],"date-time":"2021-02-26T01:08:32Z","timestamp":1614301712000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-020-04785-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,27]]},"references-count":19,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2020,4]]}},"alternative-id":["4785"],"URL":"https:\/\/doi.org\/10.1007\/s00521-020-04785-y","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,2,27]]},"assertion":[{"value":"27 February 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}