{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T16:06:14Z","timestamp":1772553974952,"version":"3.50.1"},"reference-count":17,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,7]]},"DOI":"10.1109\/ithings\/greencom\/cpscom\/smartdata.2019.00206","type":"proceedings-article","created":{"date-parts":[[2019,10,21]],"date-time":"2019-10-21T19:56:05Z","timestamp":1571687765000},"page":"1233-1240","source":"Crossref","is-referenced-by-count":28,"title":["Deep Learning for Asphyxiated Infant Cry Classification Based on Acoustic Features and Weighted Prosodic Features"],"prefix":"10.1109","author":[{"given":"Chunyan","family":"Ji","sequence":"first","affiliation":[]},{"given":"Xueli","family":"Xiao","sequence":"additional","affiliation":[]},{"given":"Sunitha","family":"Basodi","sequence":"additional","affiliation":[]},{"given":"Yi","family":"Pan","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","article-title":"The Characteristic of Infant cries","author":"lei","year":"2011","journal-title":"National Conference on Man-Machine Speech Communication"},{"key":"ref11","article-title":"Infant Cry Analysis and Detection","author":"lavner","year":"2012","journal-title":"IEEE 27th Convention of Electrical and Electronics Engineers in Israel"},{"key":"ref12","first-page":"679","article-title":"An Investigation into Classification of Infant Cries using Modified Signal Processing Methods","author":"varma","year":"2015","journal-title":"International Conference on Signal Processing and Integrated Networks"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1007\/s10916-010-9591-z","article-title":"Analysis of Infant Cry Through Weighted Linear Prediction Cepstral Coefficients and Probabilistic Neural Networks","volume":"36","author":"chee","year":"2012","journal-title":"Journal of Medical System"},{"key":"ref14","first-page":"992","article-title":"Infant Cry Detection in Adverse Acoustic Environments by Using Deep Neural Networks","author":"severini","year":"2018","journal-title":"26th European Signal Processing Conference"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TASSP.1980.1163420"},{"key":"ref16","author":"boersma","year":"0"},{"key":"ref17","year":"0"},{"key":"ref4","first-page":"986","article-title":"Orthogonal Least Square Based Support Vector Machine for the Classification of Infant Cry with Asphyxia","author":"mansor","year":"2010","journal-title":"2nd International Conference on Biomedical Engineering and Informatics"},{"key":"ref3","article-title":"A System for the Processing of Infant Cry to Recognize Pathologies in Recently Born Babies with Neural Networks","author":"reyes-galaviz","year":"2004","journal-title":"SPECOM 2004 9th conference"},{"key":"ref6","article-title":"Ubenwa: Cry-based Diagnosis of Birth Asphyxia","author":"udeogu","year":"2017","journal-title":"31st Conference on Neural Information Processing Systems"},{"key":"ref5","first-page":"485","article-title":"Detection of Asphyxiated Infant Cry using Support Vector Machine Integrated with Principal Component Analysis","author":"lee","year":"2010","journal-title":"Proceedings of IEEE EMBS Conference on Biomedical Engineering & Sciences"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCT.2018.8356861"},{"key":"ref7","first-page":"768","article-title":"Detection of Asphyxia in infants using Deep Learning Convoluational Nerral Network(CNN) Trained on Mel Frequency Cepstrum Coefficient (MFCC) Features Extracted from Cry Sounds","volume":"9","author":"yassin","year":"2017","journal-title":"Journal of Fundermental and Applied Sciences"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCSP.2018.8524517"},{"key":"ref1","first-page":"236","article-title":"Identification of Asphyxia in Newborns using GPU for Deep Learning","author":"sachin","year":"2017","journal-title":"The 2nd International Conference on Convergence Technology"},{"key":"ref9","first-page":"182","article-title":"Machine Learning Approach for Infant Cry Interpretation","author":"hamidi","year":"2017","journal-title":"International Conference on Tools with Artificial Intelligence"}],"event":{"name":"2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)","location":"Atlanta, GA, USA","start":{"date-parts":[[2019,7,14]]},"end":{"date-parts":[[2019,7,17]]}},"container-title":["2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8867850\/8875257\/08875427.pdf?arnumber=8875427","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,19]],"date-time":"2022-07-19T16:22:24Z","timestamp":1658247744000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8875427\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/ithings\/greencom\/cpscom\/smartdata.2019.00206","relation":{},"subject":[],"published":{"date-parts":[[2019,7]]}}}