Voksel tabanli 3-b nesnelerin siniflandirilmasi için evrişimsel sinir aǧlari odakli bir yaklaşim

Ridvan Sirma; Berkan Dinar; Yusuf Huseyin Sahin; Gozde Unal

doi:10.1109/SIU.2018.8404568

Voksel tabanli 3-b nesnelerin siniflandirilmasi için evrişimsel sinir aǧlari odakli bir yaklaşim

Translated title of the contribution: A convolutional neural networks oriented approach for voxel-based 3D object classification

Ridvan Sirma, Berkan Dinar, Yusuf Huseyin Sahin, Gozde Unal

Istanbul Technical University

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

1 Citation (Scopus)

Abstract

In our work, 3D objects classification has been dealt with convolutional neural networks which is a common paradigm recently in image recognition. In the first phase of experiments, 3D models in ModelNet10 and ModelNet40 data sets were voxelized and scaled with certain parameters. Classical CNN and 3D Dense CNN architectures were designed for training the pre-processed data. In addition, the two trained CNNs were ensembled and the results of them were observed. A success rate of 95.37% achieved on ModelNet10 by using 3D dense CNN, a success rate of 91.24% achieved with ensemble of two CNNs on ModelNet40.

Translated title of the contribution	A convolutional neural networks oriented approach for voxel-based 3D object classification
Original language	Turkish
Title of host publication	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-4
Number of pages	4
ISBN (Electronic)	9781538615010
DOIs	https://doi.org/10.1109/SIU.2018.8404568
Publication status	Published - 5 Jul 2018
Event	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 - Izmir, Turkey Duration: 2 May 2018 → 5 May 2018

Publication series

Name	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

Conference

Conference	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Country/Territory	Turkey
City	Izmir
Period	2/05/18 → 5/05/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Access to Document

10.1109/SIU.2018.8404568

Cite this

Sirma, R., Dinar, B., Sahin, Y. H., & Unal, G. (2018). Voksel tabanli 3-b nesnelerin siniflandirilmasi için evrişimsel sinir aǧlari odakli bir yaklaşim. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 (pp. 1-4). (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2018.8404568

Sirma, Ridvan ; Dinar, Berkan ; Sahin, Yusuf Huseyin et al. / Voksel tabanli 3-b nesnelerin siniflandirilmasi için evrişimsel sinir aǧlari odakli bir yaklaşim. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-4 (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018).

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abstract = "In our work, 3D objects classification has been dealt with convolutional neural networks which is a common paradigm recently in image recognition. In the first phase of experiments, 3D models in ModelNet10 and ModelNet40 data sets were voxelized and scaled with certain parameters. Classical CNN and 3D Dense CNN architectures were designed for training the pre-processed data. In addition, the two trained CNNs were ensembled and the results of them were observed. A success rate of 95.37% achieved on ModelNet10 by using 3D dense CNN, a success rate of 91.24% achieved with ensemble of two CNNs on ModelNet40.",

keywords = "3D object classification, Convolutional neural networks, Deep learning",

author = "Ridvan Sirma and Berkan Dinar and Sahin, {Yusuf Huseyin} and Gozde Unal",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 ; Conference date: 02-05-2018 Through 05-05-2018",

year = "2018",

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Sirma, R, Dinar, B, Sahin, YH & Unal, G 2018, Voksel tabanli 3-b nesnelerin siniflandirilmasi için evrişimsel sinir aǧlari odakli bir yaklaşim. in 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Izmir, Turkey, 2/05/18. https://doi.org/10.1109/SIU.2018.8404568

Voksel tabanli 3-b nesnelerin siniflandirilmasi için evrişimsel sinir aǧlari odakli bir yaklaşim. / Sirma, Ridvan; Dinar, Berkan; Sahin, Yusuf Huseyin et al.
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-4 (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018).

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

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AU - Sirma, Ridvan

AU - Dinar, Berkan

AU - Sahin, Yusuf Huseyin

AU - Unal, Gozde

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AB - In our work, 3D objects classification has been dealt with convolutional neural networks which is a common paradigm recently in image recognition. In the first phase of experiments, 3D models in ModelNet10 and ModelNet40 data sets were voxelized and scaled with certain parameters. Classical CNN and 3D Dense CNN architectures were designed for training the pre-processed data. In addition, the two trained CNNs were ensembled and the results of them were observed. A success rate of 95.37% achieved on ModelNet10 by using 3D dense CNN, a success rate of 91.24% achieved with ensemble of two CNNs on ModelNet40.

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KW - Convolutional neural networks

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Sirma R, Dinar B, Sahin YH , Unal G. Voksel tabanli 3-b nesnelerin siniflandirilmasi için evrişimsel sinir aǧlari odakli bir yaklaşim. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-4. (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). doi: 10.1109/SIU.2018.8404568

Voksel tabanli 3-b nesnelerin siniflandirilmasi için evrişimsel sinir aǧlari odakli bir yaklaşim

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