Abstract
In this paper, we propose a user selection based backpropagation method for siamese networks which we will use as visual filters in mobile contents. The loss function used to train the network is affected by the user’s interaction which also affects the update of the weights in the network such that the visual filter takes subjective similarities into account. As a specific application of the proposed algorithm, we expect that the visual filter can be applied for mobile services which provides the user with 3D visual products appearing above the phone. The products appearing in sequence to the user are those which have similar appearances to that selected by the user where the subjective similarity is also taken into account.
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Acknowledgments
This work was partly supported by the Industrial-Academic Cooperative R&D Program funded by the Small and Medium Business Administration (SMBA, Korea) [C0395100] and “Dongseo Frontier Project” Research Fund of 2015.
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Park, H., Lee, S. (2017). User Selection Based Backpropagation for Siamese Neural Networks in Visual Filters. In: Park, J., Chen, SC., Raymond Choo, KK. (eds) Advanced Multimedia and Ubiquitous Engineering. FutureTech MUE 2017 2017. Lecture Notes in Electrical Engineering, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-10-5041-1_19
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DOI: https://doi.org/10.1007/978-981-10-5041-1_19
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