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How transferable are features in deep neural networks? In: Ghahramani Z, Welling M, Cortes C, Lawrence ND, Weinberger KQ, editors. Advances in Neural Information Processing Systems 27. Curran Associates, Inc.; 2014. p. 3320\u20133328. Available from: <ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/papers.nips.cc\/paper\/5347-how-transferable-are-features-in-deep-neural-networks.pdf\" xlink:type=\"simple\">http:\/\/papers.nips.cc\/paper\/5347-how-transferable-are-features-in-deep-neural-networks.pdf<\/ext-link>."},{"key":"ref4","first-page":"234","article-title":"Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI 2015","author":"O Ronneberger","year":"2015"},{"issue":"3","key":"ref5","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","article-title":"ImageNet Large Scale Visual Recognition Challenge","volume":"115","author":"O Russakovsky","year":"2015","journal-title":"International Journal of Computer Vision"},{"issue":"1","key":"ref6","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1148\/radiol.2017170236","article-title":"Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs","volume":"287","author":"DB Larson","year":"2018","journal-title":"Radiology"},{"issue":"4-5","key":"ref7","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.compmedimag.2007.02.012","article-title":"Bone age assessment of children using a digital hand atlas","volume":"31","author":"A Gertych","year":"2007","journal-title":"Computerized Medical Imaging and Graphics"},{"key":"ref8","unstructured":"Abadi M, Barham P, Chen J, Chen Z, Davis A, Dean J, et al. TensorFlow: A system for large-scale machine learning. In: 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16); 2016. p. 265\u2013283. Available from: <ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/www.usenix.org\/system\/files\/conference\/osdi16\/osdi16-abadi.pdf\" xlink:type=\"simple\">https:\/\/www.usenix.org\/system\/files\/conference\/osdi16\/osdi16-abadi.pdf<\/ext-link>."},{"key":"ref9","unstructured":"Ren S, He K, Girshick R, Sun J. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. In: Cortes C, Lawrence ND, Lee DD, Sugiyama M, Garnett R, editors. Advances in Neural Information Processing Systems 28. Curran Associates, Inc.; 2015. p. 91\u201399."},{"key":"ref10","unstructured":"Szegedy C, Ioffe S, Vanhoucke V, Alemi AA. Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning. In: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA.; 2017. p. 4278\u20134284. Available from: <ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/aaai.org\/ocs\/index.php\/AAAI\/AAAI17\/paper\/view\/14806\" xlink:type=\"simple\">http:\/\/aaai.org\/ocs\/index.php\/AAAI\/AAAI17\/paper\/view\/14806<\/ext-link>."},{"key":"ref11","first-page":"740","article-title":"Computer Vision\u2014ECCV 2014","author":"TY Lin","year":"2014"},{"key":"ref12","unstructured":"Huang J, Rathod V, Sun C, Zhu M, Korattikara A, Fathi A, et al. Speed\/Accuracy Trade-Offs for Modern Convolutional Object Detectors. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR); 2017. p. 7310\u20137319. Available from: <ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/doi.ieeecomputersociety.org\/10.1109\/CVPR.2017.351\" xlink:type=\"simple\">http:\/\/doi.ieeecomputersociety.org\/10.1109\/CVPR.2017.351<\/ext-link>."},{"issue":"3","key":"ref13","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/S0734-189X(87)80186-X","article-title":"Adaptive histogram equalization and its variations","volume":"39","author":"SM Pizer","year":"1987","journal-title":"Computer Vision, Graphics, and Image Processing"},{"key":"ref14","unstructured":"Glorot X, Bengio Y. Understanding the difficulty of training deep feedforward neural networks. In: Proceedings of the thirteenth international conference on artificial intelligence and statistics; 2010. p. 249\u2013256."},{"issue":"2","key":"ref15","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","article-title":"The Pascal Visual Object Classes (VOC) Challenge","volume":"88","author":"M Everingham","year":"2010","journal-title":"International Journal of Computer Vision"},{"key":"ref16","unstructured":"Fischer B, Brosig A, Deserno TM, Ott B, G\u00fcnther RW. Structural scene analysis and content-based image retrieval applied to bone age assessment. In: Proceedings of SPIE\u2014The International Society of Optical Engineering. vol. 7260; 2009. Available from: <ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/doi.org\/10.1117\/12.811632\" xlink:type=\"simple\">https:\/\/doi.org\/10.1117\/12.811632<\/ext-link>."},{"key":"ref17","first-page":"179","article-title":"Bildverarbeitung f\u00fcr die Medizin 2017","author":"AO Mader","year":"2017"},{"issue":"2","key":"ref18","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1037\/0033-2909.88.2.322","article-title":"Integration and generalization of kappas for multiple raters","volume":"88","author":"AJ Conger","year":"1980","journal-title":"Psychological Bulletin"},{"key":"ref19","article-title":"Assessment of skeletal maturity and prediction of adult height: TW2 method","author":"JM Tanner","year":"1983"},{"issue":"9","key":"ref20","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1016\/j.mri.2012.05.001","article-title":"3D Slicer as an image computing platform for the Quantitative Imaging Network","volume":"30","author":"A Fedorov","year":"2012","journal-title":"Magnetic resonance imaging"},{"key":"ref21","first-page":"204","article-title":"Human Biology","author":"RM Acheson","year":"1966"},{"issue":"1","key":"ref22","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1109\/TMI.2008.926067","article-title":"The BoneXpert method for automated determination of skeletal maturity","volume":"28","author":"HH Thodberg","year":"2009","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"ref23","doi-asserted-by":"crossref","unstructured":"Mansourvar M, Ismail MA, Herawan T, Gopal Raj R, Abdul Kareem S, Nasaruddin FH. Automated Bone Age Assessment: Motivation, Taxonomies, and Challenges. Computational and Mathematical Methods in Medicine. vol 2013, Article ID 391626;2013.","DOI":"10.1155\/2013\/391626"},{"key":"ref24","unstructured":"Lee S, Choi M, Choi Hs, Park MS, Yoon S. FingerNet: Deep learning-based robust finger joint detection from radiographs. In: Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE. IEEE; 2015. p. 1\u20134."},{"key":"ref25","doi-asserted-by":"crossref","unstructured":"\u0160tern D, Payer C, Lepetit V, Urschler M. Automated age estimation from hand MRI volumes using deep learning. In: International Conference on Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI 2016. Springer; 2016. p. 194\u2013202.","DOI":"10.1007\/978-3-319-46723-8_23"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.media.2016.10.010","article-title":"Deep learning for automated skeletal bone age assessment in X-ray images","volume":"36","author":"C Spampinato","year":"2017","journal-title":"Medical Image Analysis"},{"issue":"4","key":"ref27","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1007\/s10278-017-9955-8","article-title":"Fully Automated Deep Learning System for Bone Age Assessment","volume":"30","author":"H Lee","year":"2017","journal-title":"Journal of Digital Imaging"},{"issue":"3","key":"ref28","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1006\/cbmr.1995.1016","article-title":"Automatic Analysis of Hand Radiographs for the Assessment of Skeletal Age: A Subsymbolic Approach","volume":"28","author":"M Rucci","year":"1995","journal-title":"Computers and Biomedical Research"},{"key":"ref29","unstructured":"Girshick R, Donahue J, Darrell T, Malik J. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation. In: Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition. CVPR\u201914. Washington, DC, USA: IEEE Computer Society; 2014. p. 580\u2013587. Available from: <ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/dx.doi.org\/10.1109\/CVPR.2014.81\" xlink:type=\"simple\">http:\/\/dx.doi.org\/10.1109\/CVPR.2014.81<\/ext-link>."},{"key":"ref30","doi-asserted-by":"crossref","unstructured":"Girshick R. Fast R-CNN. In: 2015 IEEE International Conference on Computer Vision (ICCV); 2015. p. 1440\u20131448.","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref31","doi-asserted-by":"crossref","unstructured":"Liu W, Anguelov D, Erhan D, Szegedy C, Reed S, Fu CY, et al. SSD: Single Shot MultiBox Detector. In: Leibe B, Matas J, Sebe N, Welling M, editors. Computer Vision\u2014ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part I (Lecture Notes in Computer Science). Springer International Publishing; 2016. p. 21\u201337.","DOI":"10.1007\/978-3-319-46448-0_2"},{"issue":"2","key":"ref32","first-page":"88","article-title":"Radiographic Evaluation of Skeletal Maturation","volume":"52","author":"LS Fishman","year":"1982","journal-title":"The Angle Orthodontist"},{"key":"ref33","article-title":"Advances in Computer Vision and Pattern Recognition","author":"G Csurka","year":"2017"}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/dx.plos.org\/10.1371\/journal.pone.0207496","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,9]],"date-time":"2020-05-09T16:32:40Z","timestamp":1589041960000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0207496"}},"subtitle":[],"editor":[{"given":"Kayvan","family":"Najarian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2018,11,16]]},"references-count":33,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2018,11,16]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0207496","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,11,16]]}}}