Finger-vein Recognition using Deep Fully Convolutional Neural Semantic Segmentation Networks: The Impact of Training Data

Ehsaneddin Jalilian, Andreas Uhl

Research output: Chapter in Book/Report/Conference proceeding/Legal commentary › Conference contribution › peer-review

Translated title of the contribution	Finger-vein Recognition using Deep Fully Convolutional Neural Semantic Segmentation Networks: The Impact of Training Data
Original language	English
Title of host publication	Proceedings of the IEEE 10th International Workshop on Information Forensics and Security (WIFS 2018)
Publisher	IEEE
Number of pages	8
Publication status	Published - 2018

Fields of Science and Technology Classification 2012

@inproceedings{9112bd1177dc4e7c9624b18ff7a845e2,

title = "Finger-vein Recognition using Deep Fully Convolutional Neural Semantic Segmentation Networks: The Impact of Training Data",

author = "Ehsaneddin Jalilian and Andreas Uhl",

year = "2018",

language = "English",

booktitle = "Proceedings of the IEEE 10th International Workshop on Information Forensics and Security (WIFS 2018)",

publisher = "IEEE",

}

Finger-vein Recognition using Deep Fully Convolutional Neural Semantic Segmentation Networks: The Impact of Training Data. / Jalilian, Ehsaneddin; Uhl, Andreas.
Proceedings of the IEEE 10th International Workshop on Information Forensics and Security (WIFS 2018). IEEE, 2018.

Research output: Chapter in Book/Report/Conference proceeding/Legal commentary › Conference contribution › peer-review

TY - GEN

T1 - Finger-vein Recognition using Deep Fully Convolutional Neural Semantic Segmentation Networks: The Impact of Training Data

AU - Jalilian, Ehsaneddin

AU - Uhl, Andreas

PY - 2018

Y1 - 2018

UR - http://wavelab.at/papers/Jalilian18a.pdf

M3 - Conference contribution

BT - Proceedings of the IEEE 10th International Workshop on Information Forensics and Security (WIFS 2018)

PB - IEEE

ER -