Özkan, Akın

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https://hdl.handle.net/20.500.14411/7674
Name Variants
Ö.,Akın
Özkan,A.
Akin, Ozkan
Akın, Özkan
A.,Özkan
Ozkan,A.
A.,Ozkan
O.,Akin
O., Akin
A., Ozkan
Özkan, Akın
Ozkan, Akin
Job Title
Araştırma Görevlisi
Email Address
akin.ozkan@atilim.edu.tr
Main Affiliation
Department of Electrical & Electronics Engineering
Status
Former Staff
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Scholarly Output

10

Articles

3

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26

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37

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2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 -- 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 -- 20 April 2011 through 22 April 2011 -- Antalya -- 855281
2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings -- 24th Signal Processing and Communication Application Conference, SIU 2016 -- 16 May 2016 through 19 May 2016 -- Zonguldak -- 1226051
24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY1
25th IEEE International Conference on Image Processing (ICIP) -- OCT 07-10, 2018 -- Athens, GREECE1
Biomedical Research (India)1
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Start date: 2011Subject: Kinship Synthesis

Scholarly Output Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 23
    Kinshipgan: Synthesizing of Kinship Faces From Family Photos by Regularizing a Deep Face Network
    (IEEE Computer Society, 2018) Ozkan,S.; Ozkan,A.
    In this paper, we propose a kinship generator network that can synthesize a possible child face by analyzing his/her parent's photo. For this purpose, we focus on to handle the scarcity of kinship datasets throughout the paper by proposing novel solutions in particular. To extract robust features, we integrate a pre-trained face model to the kinship face generator. Moreover, the generator network is regularized with an additional face dataset and adversarial loss to decrease the overfitting of the limited samples. Lastly, we adapt cycle-domain transformation to attain a more stable results. Experiments are conducted on Families in the Wild (FIW) dataset. The experimental results show that the contributions presented in the paper provide important performance improvements compared to the baseline architecture and our proposed method yields promising perceptual results. © 2018 IEEE.
  • Thumbnail Image
    Conference Object
    Citation - WoS: 16
    KINSHIPGAN: SYNTHESIZING OF KINSHIP FACES FROM FAMILY PHOTOS BY REGULARIZING A DEEP FACE NETWORK
    (Ieee, 2018) Ozkan, Savas; Ozkan, Akin
    In this paper, we propose a kinship generator network that can synthesize a possible child face by analyzing his/her parent's photo. For this purpose, we focus on to handle the scarcity of kinship datasets throughout the paper by proposing novel solutions in particular. To extract robust features, we integrate a pre-trained face model to the kinship face generator. Moreover, the generator network is regularized with an additional face dataset and adversarial loss to decrease the overfitting of the limited samples. Lastly, we adapt cycle-domain transformation to attain a more stable results. Experiments are conducted on Families in the Wild (FIW) dataset. The experimental results show that the contributions presented in the paper provide important performance improvements compared to the baseline architecture and our proposed method yields promising perceptual results.