TY - GEN
T1 - Deep domain adaption for convolutional neural network (CNN) based iris segmentation
T2 - 2019 International Conference of the Biometrics Special Interest Group, BIOSIG 2019
AU - Jalilian, Ehsaneddin
AU - Uhl, Andreas
PY - 2019/9/1
Y1 - 2019/9/1
N2 - Addressing the lack of massive amounts of labeled training data, deep domain adaptation has been applied successfully in many applications of machine learning. We investigate the application of deep domain adaptation for CNN based iris segmentation, exploring available solutions and their corresponding strengths and pitfalls, with several major contributions. First, we provide a comprehensive survey of current deep domain adaptation methods according to the properties of data that cause the domains divergence. Second, after selecting credible methods, we evaluate their expedience in terms of iris segmentation performance. Third, we analyze and compare the performance against the state-of-the-art methods under these categories. Forth, potential shortfalls of current methods and several future directions are pointed out and discussed.
AB - Addressing the lack of massive amounts of labeled training data, deep domain adaptation has been applied successfully in many applications of machine learning. We investigate the application of deep domain adaptation for CNN based iris segmentation, exploring available solutions and their corresponding strengths and pitfalls, with several major contributions. First, we provide a comprehensive survey of current deep domain adaptation methods according to the properties of data that cause the domains divergence. Second, after selecting credible methods, we evaluate their expedience in terms of iris segmentation performance. Third, we analyze and compare the performance against the state-of-the-art methods under these categories. Forth, potential shortfalls of current methods and several future directions are pointed out and discussed.
KW - Convolutional neural networks
KW - Deep domain adaptation
KW - Iris segmentation
UR - http://www.scopus.com/inward/record.url?scp=85075880356&partnerID=8YFLogxK
M3 - Conference contribution
T3 - 2019 International Conference of the Biometrics Special Interest Group, BIOSIG 2019 - Proceedings
BT - 2019 International Conference of the Biometrics Special Interest Group, BIOSIG 2019 - Proceedings
A2 - Bromme, Bromme
A2 - Busch, Christoph
A2 - Dantcheva, Antitza
A2 - Rathgeb, Christian
A2 - Uhl, Andreas
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 18 September 2019 through 20 September 2019
ER -