The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
pandangan teks lengkap
81
Pengecaman urat tangan-dorsa diselesaikan berdasarkan pengaktifan konvolusi rangkaian saraf konvolusi dalam (DCNN) yang telah terlatih. Secara khusus, pengumpulan rentas konvolusional khusus tugasan baru dicadangkan untuk mendapatkan perwakilan ciri yang lebih representatif dan diskriminatif. Eksperimen yang ketat pada pangkalan data yang diwujudkan sendiri mencapai hasil pengiktirafan terkini, yang menunjukkan keberkesanan model yang dicadangkan.
Jun WANG
China University of Mining and Technology
Yulian LI
China University of Mining and Technology
Zaiyu PAN
China University of Mining and Technology
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Salinan
Jun WANG, Yulian LI, Zaiyu PAN, "Hand-Dorsa Vein Recognition Based on Task-Specific Cross-Convolutional-Layer Pooling" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 12, pp. 2628-2631, December 2019, doi: 10.1587/transinf.2019EDL8119.
Abstract: Hand-dorsa vein recognition is solved based on the convolutional activations of the pre-trained deep convolutional neural network (DCNN). In specific, a novel task-specific cross-convolutional-layer pooling is proposed to obtain the more representative and discriminative feature representation. Rigorous experiments on the self-established database achieves the state-of-the-art recognition result, which demonstrates the effectiveness of the proposed model.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019EDL8119/_p
Salinan
@ARTICLE{e102-d_12_2628,
author={Jun WANG, Yulian LI, Zaiyu PAN, },
journal={IEICE TRANSACTIONS on Information},
title={Hand-Dorsa Vein Recognition Based on Task-Specific Cross-Convolutional-Layer Pooling},
year={2019},
volume={E102-D},
number={12},
pages={2628-2631},
abstract={Hand-dorsa vein recognition is solved based on the convolutional activations of the pre-trained deep convolutional neural network (DCNN). In specific, a novel task-specific cross-convolutional-layer pooling is proposed to obtain the more representative and discriminative feature representation. Rigorous experiments on the self-established database achieves the state-of-the-art recognition result, which demonstrates the effectiveness of the proposed model.},
keywords={},
doi={10.1587/transinf.2019EDL8119},
ISSN={1745-1361},
month={December},}
Salinan
TY - JOUR
TI - Hand-Dorsa Vein Recognition Based on Task-Specific Cross-Convolutional-Layer Pooling
T2 - IEICE TRANSACTIONS on Information
SP - 2628
EP - 2631
AU - Jun WANG
AU - Yulian LI
AU - Zaiyu PAN
PY - 2019
DO - 10.1587/transinf.2019EDL8119
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2019
AB - Hand-dorsa vein recognition is solved based on the convolutional activations of the pre-trained deep convolutional neural network (DCNN). In specific, a novel task-specific cross-convolutional-layer pooling is proposed to obtain the more representative and discriminative feature representation. Rigorous experiments on the self-established database achieves the state-of-the-art recognition result, which demonstrates the effectiveness of the proposed model.
ER -