{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T03:52:45Z","timestamp":1648785165191},"reference-count":12,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. &amp; Syst."],"published-print":{"date-parts":[[2020,6,1]]},"DOI":"10.1587\/transinf.2019edl8204","type":"journal-article","created":{"date-parts":[[2020,5,31]],"date-time":"2020-05-31T22:09:44Z","timestamp":1590962984000},"page":"1423-1426","source":"Crossref","is-referenced-by-count":1,"title":["Hand-Dorsa Vein Recognition Based on Selective Deep Convolutional Feature"],"prefix":"10.1587","volume":"E103.D","author":[{"given":"Zaiyu","family":"PAN","sequence":"first","affiliation":[{"name":"School of Information and Control Engineering, China University of Mining and Technology"}]},{"given":"Jun","family":"WANG","sequence":"additional","affiliation":[{"name":"School of Information and Control Engineering, China University of Mining and Technology"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] Y. Fang, Q. Wu, and W. Kang, \u201cA novel finger vein verification system based on two-stream convolutional network learning,\u201d Neurocomputing, vol.290, pp.100-107, 2018. 10.1016\/j.neucom.2018.02.042","DOI":"10.1016\/j.neucom.2018.02.042"},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] J. Wang and G. Wang, \u201cHand-dorsa vein recognition with structure growing guided CNN,\u201d OPTIK, vol.149, pp.469-477, 2017. 10.1016\/j.ijleo.2017.09.064","DOI":"10.1016\/j.ijleo.2017.09.064"},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] P. Agrawal, R. Girshick, and J. Malik, \u201cAnalyzing the performance of multilayer neural networks for object recognition,\u201d Proc. Eur. Conf. Comp. Vis., 2014.","DOI":"10.1007\/978-3-319-10584-0_22"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] M. Zeiler and R. Fergus, \u201cVisualizing and understanding convolutional networks,\u201d Proc. Eur. Conf. Comp. Vis., 2014.","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"5","doi-asserted-by":"publisher","unstructured":"[5] X.-S. Wei, J.-H. Luo, J. Wu, and Z.-H. Zhou, \u201cSelective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval,\u201d IEEE Trans. Image Process., vol.26, no.6, pp.2868-2881, 2017. 10.1109\/tip.2017.2688133","DOI":"10.1109\/TIP.2017.2688133"},{"key":"6","unstructured":"[6] J. Wang, G. Wang, M. Li, K. Wang, and H. Tian, \u201cHand vein recognition based on improved template matching,\u201d Int. J. Bioautomation, vol.18, no.4, pp.337-348, Dec. 2014."},{"key":"7","unstructured":"[7] K. Simonyan and A. Zisserman, \u201cVery Deep Convolutional Networks for Large-Scale Image Recognition,\u201d arXiv: 1409.1556, 2014."},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] L. Liu, C. Shen, and A. van den Hengel, \u201cCross-Convolutional-Layer Pooling for Image Recognition,\u201d IEEE Trans. Pattern Anal. Mach. Intell., vol.39, no.11, pp.2305-2313, Nov. 2017. 10.1109\/tpami.2016.2637921","DOI":"10.1109\/TPAMI.2016.2637921"},{"key":"9","unstructured":"[9] H. Hai, L. Chen, H. Song, and J. Yang, \u201cDorsal hand vein recognition based on convolutional neural networks,\u201d 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2017."},{"key":"10","doi-asserted-by":"publisher","unstructured":"[10] N. Al-johania and L. Elrefaei, \u201cDorsa Hand Vein Recognition by Convolutional Neural Networks: Feature Learning and Transfer Learning Approaches,\u201d International Journal of Intelligent Engineering and Systems, vol.12, no.3, pp.178-191, 2019. 10.22266\/ijies2019.0630.19","DOI":"10.22266\/ijies2019.0630.19"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] J. Wang, G. Wang, and M. Zhou, \u201cBimodal Vein Data Mining via Cross-Selective-Domain Knowledge Transfer,\u201d IEEE Trans. Inf. Forensics Security, vol.13, no.3, pp.733-744, March 2018. 10.1109\/tifs.2017.2766039","DOI":"10.1109\/TIFS.2017.2766039"},{"key":"12","doi-asserted-by":"publisher","unstructured":"[12] J. Wang, K. Yang, Z. Pan, G. Wang, M. Li, and Y. Li, \u201cMinutiae-Based Weighting Aggregation of Deep Convolutional Features for Vein Recognition,\u201d IEEE Access, vol.6, pp.61640-61650, 2018. 10.1109\/access.2018.2876396","DOI":"10.1109\/ACCESS.2018.2876396"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E103.D\/6\/E103.D_2019EDL8204\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,6,6]],"date-time":"2020-06-06T03:25:17Z","timestamp":1591413917000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E103.D\/6\/E103.D_2019EDL8204\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,1]]},"references-count":12,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2020]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2019edl8204","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,1]]}}}