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Shape Classification Using Combined Features

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Book cover Computational Collective Intelligence (ICCCI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10449))

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Abstract

Shape classification is an active research field due to its usefulness. In this work, hand crafted shape descriptors are combined with features extracted using convolutional neural network to do the classifi cation task. Extensive experiments were performed on public data sets to reveal the performance of the proposed method compared to the other state of the arts shape classification methods.

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    https://www.mpi-inf.mpg.de/departments/computer-vision-and-multimodal-computing/research/object-recognition-and-scene-understanding/analyzing-appearance-and-contour-based-methods-for-object-categorization/.

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Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korean Government (2016R1D1A1A02937579).

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Correspondence to Laksono Kurnianggoro .

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Kurnianggoro, L., Wahyono, Filonenko, A., Jo, KH. (2017). Shape Classification Using Combined Features. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10449. Springer, Cham. https://doi.org/10.1007/978-3-319-67077-5_53

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  • DOI: https://doi.org/10.1007/978-3-319-67077-5_53

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