{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:31:04Z","timestamp":1772119864343,"version":"3.50.1"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T00:00:00Z","timestamp":1673222400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T00:00:00Z","timestamp":1673222400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP16H06302, JP18H04120, JP20K23355, JP21H04907, JP21K18023"],"award-info":[{"award-number":["JP16H06302, JP18H04120, JP20K23355, JP21H04907, JP21K18023"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002241","name":"Japan Science and Technology Agency","doi-asserted-by":"publisher","award":["JPMJCR18A6, JPMJCR20D3"],"award-info":[{"award-number":["JPMJCR18A6, JPMJCR20D3"]}],"id":[{"id":"10.13039\/501100002241","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Telecommun Syst"],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1007\/s11235-022-00985-0","type":"journal-article","created":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T15:02:11Z","timestamp":1673276531000},"page":"301-313","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["On the predictability in reversible steganography"],"prefix":"10.1007","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7723-4591","authenticated-orcid":false,"given":"Ching-Chun","family":"Chang","sequence":"first","affiliation":[]},{"given":"Xu","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Sisheng","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Hitoshi","family":"Kiya","sequence":"additional","affiliation":[]},{"given":"Isao","family":"Echizen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,9]]},"reference":[{"key":"985_CR1","unstructured":"Goodfellow, I., Shlens, J., & Szegedy, C. (2015). Explaining and harnessing adversarial examples. In Proceedings of international conference on learning representations (ICLR), San Diego, CA, USA (pp. 1\u201311)."},{"key":"985_CR2","doi-asserted-by":"crossref","unstructured":"Moosavi-Dezfooli, S.-M., Fawzi, A., & Frossard, P. (2016). DeepFool: A simple and accurate method to fool deep neural networks. In Proceedings of IEEE conference on computer vision and pattern recognition (CVPR), Las Vegas, NV, USA (pp. 2574\u20132582).","DOI":"10.1109\/CVPR.2016.282"},{"key":"985_CR3","doi-asserted-by":"crossref","unstructured":"Mu\u00f1oz-Gonz\u00e1lez, L., Biggio, B., Demontis, A., Paudice, A., Wongrassamee, V., Lupu, E.\u00a0C., & Roli, F. (2017). Towards poisoning of deep learning algorithms with back-gradient optimization. In Proceedings of ACM workshop on artificial intelligence and security (AISec), Dallas, TX, USA (pp. 27\u201338).","DOI":"10.1145\/3128572.3140451"},{"issue":"4","key":"985_CR4","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1109\/49.668971","volume":"16","author":"R Anderson","year":"1998","unstructured":"Anderson, R., & Petitcolas, F. (1998). On the limits of steganography. IEEE Journal on Selected Areas in Communications, 16(4), 474\u2013481.","journal-title":"IEEE Journal on Selected Areas in Communications"},{"issue":"10","key":"985_CR5","doi-asserted-by":"publisher","first-page":"1403","DOI":"10.1109\/5.959338","volume":"89","author":"F Bartolini","year":"2001","unstructured":"Bartolini, F., Tefas, A., Barni, M., & Pitas, I. (2001). Image authentication techniques for surveillance applications. Proceedings of the IEEE, 89(10), 1403\u20131418.","journal-title":"Proceedings of the IEEE"},{"issue":"2","key":"985_CR6","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s11235-010-9366-3","volume":"49","author":"M Abolfathi","year":"2012","unstructured":"Abolfathi, M., & Amirfattahi, R. (2012). Design and implementation of a reliable and authenticated satellite image communication. Telecommunication Systems, 49(2), 171\u2013177.","journal-title":"Telecommunication Systems"},{"issue":"2002","key":"985_CR7","first-page":"185","volume":"986842","author":"J Fridrich","year":"2002","unstructured":"Fridrich, J., Goljan, M., & Du, R. (2002). Lossless data embedding\u2014New paradigm in digital watermarking. EURASIP Journal on Advances in Signal Processing, 986842(2002), 185\u2013196.","journal-title":"EURASIP Journal on Advances in Signal Processing"},{"issue":"1","key":"985_CR8","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1109\/TMM.2003.809729","volume":"5","author":"C De Vleeschouwer","year":"2003","unstructured":"De Vleeschouwer, C., Delaigle, J.-F., & Macq, B. (2003). Circular interpretation of bijective transformations in lossless watermarking for media asset management. IEEE Transactions on Multimedia, 5(1), 97\u2013105.","journal-title":"IEEE Transactions on Multimedia"},{"issue":"8","key":"985_CR9","doi-asserted-by":"publisher","first-page":"890","DOI":"10.1109\/TCSVT.2003.815962","volume":"13","author":"J Tian","year":"2003","unstructured":"Tian, J. (2003). Reversible data embedding using a difference expansion. IEEE Transactions on Circuits and Systems for Video Technology, 13(8), 890\u2013896.","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"issue":"4","key":"985_CR10","doi-asserted-by":"publisher","first-page":"1042","DOI":"10.1109\/TIP.2005.863053","volume":"15","author":"MU Celik","year":"2006","unstructured":"Celik, M. U., Sharma, G., & Tekalp, A. M. (2006). Lossless watermarking for image authentication: A new framework and an implementation. IEEE Transactions on Image Processing, 15(4), 1042\u20131049.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"3","key":"985_CR11","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1109\/TCSVT.2006.869964","volume":"16","author":"Z Ni","year":"2006","unstructured":"Ni, Z., Shi, Y.-Q., Ansari, N., & Su, W. (2006). Reversible data hiding. IEEE Transactions on Circuits and Systems for Video Technology, 16(3), 354\u2013362.","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"issue":"3","key":"985_CR12","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1109\/TIFS.2007.905146","volume":"2","author":"S Lee","year":"2007","unstructured":"Lee, S., Yoo, C. D., & Kalker, T. (2007). Reversible image watermarking based on integer-to-integer wavelet transform. IEEE Transactions on Information Forensics and Security, 2(3), 321\u2013330.","journal-title":"IEEE Transactions on Information Forensics and Security"},{"issue":"1","key":"985_CR13","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1109\/TIP.2011.2162424","volume":"21","author":"D Coltuc","year":"2012","unstructured":"Coltuc, D. (2012). Low distortion transform for reversible watermarking. IEEE Transactions on Image Processing, 21(1), 412\u2013417.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"2","key":"985_CR14","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/s11235-010-9365-4","volume":"49","author":"G Feng","year":"2012","unstructured":"Feng, G., Qian, Z., & Zhang, X. (2012). Spectrum-estimation based lossless information recovery for sparse array patterns. Telecommunication Systems, 49(2), 163\u2013169.","journal-title":"Telecommunication Systems"},{"key":"985_CR15","doi-asserted-by":"publisher","first-page":"3210","DOI":"10.1109\/ACCESS.2016.2573308","volume":"4","author":"Y-Q Shi","year":"2016","unstructured":"Shi, Y.-Q., Li, X., Zhang, X., Wu, H., & Ma, B. (2016). Reversible data hiding: Advances in the past two decades. IEEE Access, 4, 3210\u20133237.","journal-title":"IEEE Access"},{"issue":"3","key":"985_CR16","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","volume":"27","author":"CE Shannon","year":"1948","unstructured":"Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379\u2013423.","journal-title":"Bell System Technical Journal"},{"issue":"3","key":"985_CR17","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1109\/TIP.2006.891046","volume":"16","author":"DM Thodi","year":"2007","unstructured":"Thodi, D. M., & Rodriguez, J. J. (2007). Expansion embedding techniques for reversible watermarking. IEEE Transactions on Image Processing, 16(3), 721\u2013730.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"20","key":"985_CR18","doi-asserted-by":"publisher","first-page":"870","DOI":"10.1587\/elex.5.870","volume":"5","author":"M Fallahpour","year":"2008","unstructured":"Fallahpour, M. (2008). Reversible image data hiding based on gradient adjusted prediction. IEICE Electronics Express, 5(20), 870\u2013876.","journal-title":"IEICE Electronics Express"},{"issue":"4","key":"985_CR19","doi-asserted-by":"publisher","first-page":"1779","DOI":"10.1109\/TIP.2014.2307482","volume":"23","author":"I Dragoi","year":"2014","unstructured":"Dragoi, I., & Coltuc, D. (2014). Local prediction based difference expansion reversible watermarking. IEEE Transactions on Image Processing, 23(4), 1779\u20131790.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"1","key":"985_CR20","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1186\/s13640-016-0144-3","volume":"2016","author":"HJ Hwang","year":"2016","unstructured":"Hwang, H. J., Kim, S., & Kim, H. J. (2016). Reversible data hiding using least square predictor via the LASSO. EURASIP Journal on Image and Video Processing, 2016(1), 42.","journal-title":"EURASIP Journal on Image and Video Processing"},{"key":"985_CR21","doi-asserted-by":"crossref","unstructured":"Kalker, T. & Willems, F.\u00a0M.\u00a0J. (2002). Capacity bounds and constructions for reversible data-hiding. In Proceedings of international conference on digital signal processing (DSP), Santorini, Greece (pp. 71\u201376).","DOI":"10.1109\/ICDSP.2002.1027818"},{"issue":"1","key":"985_CR22","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1007\/s11235-006-9009-x","volume":"33","author":"M Carli","year":"2006","unstructured":"Carli, M., Campisi, P., & Neri, A. (2006). Perceptual aspects in data hiding. Telecommunication Systems, 33(1), 117\u2013129.","journal-title":"Telecommunication Systems"},{"issue":"2","key":"985_CR23","first-page":"315","volume":"47","author":"J Wang","year":"2017","unstructured":"Wang, J., Ni, J., Zhang, X., & Shi, Y.-Q. (2017). Rate and distortion optimization for reversible data hiding using multiple histogram shifting. IEEE Transactions on Cybernetics, 47(2), 315\u2013326.","journal-title":"IEEE Transactions on Cybernetics"},{"key":"985_CR24","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1109\/LSP.2021.3059202","volume":"28","author":"R Hu","year":"2021","unstructured":"Hu, R., & Xiang, S. (2021). CNN prediction based reversible data hiding. IEEE Signal Processing Letters, 28, 464\u2013468.","journal-title":"IEEE Signal Processing Letters"},{"key":"985_CR25","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/5580272","volume":"2021","author":"C-C Chang","year":"2021","unstructured":"Chang, C.-C. (2021). Neural reversible steganography with long short-term memory. Security and Communication Networks, 2021, 5580272.","journal-title":"Security and Communication Networks"},{"key":"985_CR26","doi-asserted-by":"crossref","unstructured":"Tai, Y., Yang, J., Liu, X., & Xu, C. (2017). MemNet: A persistent memory network for image restoration. In Proceedings of IEEE international conference on computer vision (ICCV), Venice, Italy (pp. 4549\u20134557).","DOI":"10.1109\/ICCV.2017.486"},{"issue":"7","key":"985_CR27","doi-asserted-by":"publisher","first-page":"989","DOI":"10.1109\/TCSVT.2009.2020257","volume":"19","author":"V Sachnev","year":"2009","unstructured":"Sachnev, V., Kim, H. J., Nam, J., Suresh, S., & Shi, Y.-Q. (2009). Reversible watermarking algorithm using sorting and prediction. IEEE Transactions on Circuits and Systems for Video Technology, 19(7), 989\u2013999.","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"issue":"12","key":"985_CR28","doi-asserted-by":"publisher","first-page":"3524","DOI":"10.1109\/TIP.2011.2150233","volume":"20","author":"X Li","year":"2011","unstructured":"Li, X., Yang, B., & Zeng, T. (2011). Efficient reversible watermarking based on adaptive prediction-error expansion and pixel selection. IEEE Transactions on Image Processing, 20(12), 3524\u20133533.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"1","key":"985_CR29","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.sigpro.2011.06.006","volume":"92","author":"F Peng","year":"2012","unstructured":"Peng, F., Li, X., & Yang, B. (2012). Adaptive reversible data hiding scheme based on integer transform. Signal Processing, 92(1), 54\u201362.","journal-title":"Signal Processing"},{"issue":"7","key":"985_CR30","doi-asserted-by":"publisher","first-page":"7911","DOI":"10.1007\/s11042-018-6031-4","volume":"78","author":"F Cao","year":"2019","unstructured":"Cao, F., An, B., Yao, H., & Tang, Z. (2019). Local complexity based adaptive embedding mechanism for reversible data hiding in digital images. Multimedia Tools and Applications, 78(7), 7911\u20137926.","journal-title":"Multimedia Tools and Applications"},{"issue":"7553","key":"985_CR31","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., & Hinton, G. E. (2015). Deep learning. Nature, 521(7553), 436\u2013444.","journal-title":"Nature"},{"key":"985_CR32","first-page":"2066","volume":"30","author":"S Baluja","year":"2017","unstructured":"Baluja, S. (2017). Hiding images in plain sight: Deep steganography. Proceedings of international conference on neural information processing systems (NeurIPS), 30, 2066\u20132076.","journal-title":"Proceedings of international conference on neural information processing systems (NeurIPS)"},{"key":"985_CR33","unstructured":"Hayes, J., & Danezis, G. (2017). Generating steganographic images via adversarial training. In Proceedings of international conference on neural information processing systems (NeurIPS), Long Beach, CA, USA (pp. 2066\u20132076)"},{"issue":"10","key":"985_CR34","doi-asserted-by":"publisher","first-page":"1547","DOI":"10.1109\/LSP.2017.2745572","volume":"24","author":"W Tang","year":"2017","unstructured":"Tang, W., Tan, S., Li, B., & Huang, J. (2017). Automatic steganographic distortion learning using a generative adversarial network. IEEE Signal Processing Letters, 24(10), 1547\u20131551.","journal-title":"IEEE Signal Processing Letters"},{"key":"985_CR35","doi-asserted-by":"crossref","unstructured":"Zhu, J., Kaplan, R., Johnson, J., & Li, F.-F. (2018). HiDDeN: Hiding data with deep networks. In Proceedings of European conference on computer vision (ECCV), Munich, Germany (pp. 682\u2013697).","DOI":"10.1007\/978-3-030-01267-0_40"},{"key":"985_CR36","unstructured":"Volkhonskiy, D., Nazarov, I., & Burnaev, E. (2019). Steganographic generative adversarial networks. In Proceedings of international conference on machine vision (ICMV), Amsterdam, Netherlands (pp. 1\u201315)."},{"key":"985_CR37","doi-asserted-by":"crossref","unstructured":"Wengrowski, E., & Dana, K. (2019). Light field messaging with deep photographic steganography. In Proceedings of IEEE conference on computer vision and pattern recognition (CVPR), Long Beach, CA, USA (pp. 1515\u20131524).","DOI":"10.1109\/CVPR.2019.00161"},{"key":"985_CR38","doi-asserted-by":"crossref","unstructured":"Tancik, M., Mildenhall, B., & Ng, R. (2020). StegaStamp: Invisible hyperlinks in physical photographs. In Proceedings of IEEE\/CVF conference on computer vision and pattern recognition (CVPR), Seattle, WA, USA (pp. 2114\u20132123).","DOI":"10.1109\/CVPR42600.2020.00219"},{"key":"985_CR39","doi-asserted-by":"crossref","unstructured":"Luo, X., Zhan, R., Chang, H., Yang, F., & Milanfar, P. (2020) Distortion agnostic deep watermarking. In Proceedings of IEEE\/CVF conference on computer vision and pattern recognition (CVPR), Seattle, WA, USA (pp. 13545\u201313554).","DOI":"10.1109\/CVPR42600.2020.01356"},{"key":"985_CR40","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/4932782","volume":"2019","author":"Z Zhang","year":"2019","unstructured":"Zhang, Z., Fu, G., Di, F., Li, C., & Liu, J. (2019). Generative reversible data hiding by image-to-image translation via GANs. Security and Communication Networks, 2019, 4932782.","journal-title":"Security and Communication Networks"},{"key":"985_CR41","doi-asserted-by":"publisher","first-page":"9314","DOI":"10.1109\/ACCESS.2019.2891247","volume":"7","author":"X Duan","year":"2019","unstructured":"Duan, X., Jia, K., Li, B., Guo, D., Zhang, E., & Qin, C. (2019). Reversible image steganography scheme based on a U-Net structure. IEEE Access, 7, 9314\u20139323.","journal-title":"IEEE Access"},{"key":"985_CR42","doi-asserted-by":"crossref","unstructured":"Lu, S.-P., Wang, R., Zhong, T., & Rosin, P.\u00a0L. (2021). Large-capacity image steganography based on invertible neural networks. In Proceedings of IEEE\/CVF conference on computer vision and pattern recognition (CVPR), virtual (pp. 10816\u201310825).","DOI":"10.1109\/CVPR46437.2021.01067"},{"key":"985_CR43","doi-asserted-by":"publisher","first-page":"198425","DOI":"10.1109\/ACCESS.2020.3034936","volume":"8","author":"C-C Chang","year":"2020","unstructured":"Chang, C.-C. (2020). Adversarial learning for invertible steganography. IEEE Access, 8, 198425\u2013198435.","journal-title":"IEEE Access"},{"key":"985_CR44","unstructured":"Krizhevsky, A., Sutskever, I., & Hinton, G.\u00a0E. (2012). ImageNet classification with deep convolutional neural networks. In Proceedings of international conference on neural information processing systems (NeurIPS), Lake Tahoe, NV, USA (pp. 1097\u20131105)."},{"key":"985_CR45","unstructured":"Simonyan, K., & Zisserman, A. (2015) Very deep convolutional networks for large-scale image recognition. In Proceedings of international conference on learning representations (ICLR), San Diego, CA, USA (pp. 1\u201314)."},{"key":"985_CR46","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015). Going deeper with convolutions. In Proccedings of IEEE conference on computer vision and pattern recognition (CVPR), Boston, MA, USA (pp. 1\u20139).","DOI":"10.1109\/CVPR.2015.7298594"},{"issue":"143","key":"985_CR47","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1080\/01621459.1923.10502116","volume":"18","author":"EB Wilson","year":"1923","unstructured":"Wilson, E. B. (1923). First and second laws of error. Journal of the American Statistical Association, 18(143), 841\u2013851.","journal-title":"Journal of the American Statistical Association"},{"key":"985_CR48","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Tian, Y., Kong, Y., Zhong, B., & Fu, Y. (2018). Residual dense network for image super-resolution. In Proceedings of IEEE conference on computer vision and pattern recognition (CVPR), Salt Lake City, UT, USA (pp 2472\u20132481).","DOI":"10.1109\/CVPR.2018.00262"},{"key":"985_CR49","unstructured":"Glorot, X., Bordes, A., & Bengio, Y. (2011). Deep sparse rectifier neural networks. In Proceedings of international conference on artificial intelligence and statistics (AISTATS), Fort Lauderdale, FL, USA (pp. 315\u2013323)."},{"key":"985_CR50","unstructured":"Lin, M., Chen, Q., & Yan, S. (2014). Network in network. In Proceedings of international conference on learning representations (ICLR), Banff, AB, Canada (pp. 1\u201310)."},{"key":"985_CR51","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of IEEE conference on computer vision and pattern recognition (CVPR) (pp. 770\u2013778).","DOI":"10.1109\/CVPR.2016.90"},{"issue":"7","key":"985_CR52","doi-asserted-by":"publisher","first-page":"2480","DOI":"10.1109\/TPAMI.2020.2968521","volume":"43","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Tian, Y., Kong, Y., Zhong, B., & Fu, Y. (2021). Residual dense network for image restoration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(7), 2480\u20132495.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"985_CR53","doi-asserted-by":"crossref","unstructured":"Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323(6088), 533\u2013536.","DOI":"10.1038\/323533a0"},{"issue":"1","key":"985_CR54","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1109\/5326.827457","volume":"30","author":"C De Stefano","year":"2000","unstructured":"De Stefano, C., Sansone, C., & Vento, M. (2000). To reject or not to reject: That is the question\u2014An answer in case of neural classifiers. IEEE Transactions on Systems, Man, and Cybernetics, 30(1), 84\u201394.","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics"},{"key":"985_CR55","unstructured":"Geifman, Y., & El-Yaniv, R. (2019). SelectiveNet: A deep neural network with an integrated reject option. In Proceedings of international conference on machine learning (ICML), Long Beach, CA, USA (pp. 2151\u20132159)."},{"key":"985_CR56","unstructured":"Thulasidasan, S., Bhattacharya, T., Bilmes, J., Chennupati, G., & Mohd-Yusof, J. (2019). Combating label noise in deep learning using abstention. In Proceedings of international conference on machine learning (ICML), vol.\u00a097, Long Beach, CA, USA (pp. 6234\u20136243)."},{"issue":"1","key":"985_CR57","doi-asserted-by":"publisher","first-page":"4: 1","DOI":"10.1038\/s41746-020-00367-3","volume":"4","author":"B Kompa","year":"2021","unstructured":"Kompa, B., Snoek, J., & Beam, A. L. (2021). Second opinion needed: Communicating uncertainty in medical machine learning. NPJ Digital Medicine, 4(1), 4: 1-6.","journal-title":"NPJ Digital Medicine"},{"key":"985_CR58","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., & Brox, T. (2015). U-Net: Convolutional networks for biomedical image segmentation. In Proceedings of international conference on medical image computing and computer-assisted intervention (MICCAI), Munich, Germany (pp. 234\u2013241).","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"985_CR59","doi-asserted-by":"crossref","unstructured":"Bas, P., Filler, T., & Pevn\u00fd, T. (2011). Break our steganographic system: The ins and outs of organizing BOSS. In Proceedings of international workshop on information hiding (IH), Prague, Czech Republic (pp. 59\u201370).","DOI":"10.1007\/978-3-642-24178-9_5"},{"key":"985_CR60","unstructured":"Weber, A.\u00a0G. (2006). The USC-SIPI image database: Version 5. USC Viterbi School of Engineering, Signal and Image Processing Institute, Los Angeles, CA, USA, Technical Report, 315."}],"container-title":["Telecommunication Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11235-022-00985-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11235-022-00985-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11235-022-00985-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T13:22:46Z","timestamp":1675689766000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11235-022-00985-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,9]]},"references-count":60,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["985"],"URL":"https:\/\/doi.org\/10.1007\/s11235-022-00985-0","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-1740769\/v1","asserted-by":"object"}]},"ISSN":["1018-4864","1572-9451"],"issn-type":[{"value":"1018-4864","type":"print"},{"value":"1572-9451","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,9]]},"assertion":[{"value":"5 December 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 January 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}