CoNet: Compact and Low-Cost CNN for Image Classification

Fattah Azzuhry Rahadian; W. Wahyono; Agus Harjoko; Jia Ching Wang; Chien Yao Wang

doi:10.1109/ICCE-TW46550.2019.8991841

CoNet: Compact and Low-Cost CNN for Image Classification

Fattah Azzuhry Rahadian, W. Wahyono, Agus Harjoko, Jia Ching Wang, Chien Yao Wang

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

Abstract

As the number of applications of Convolutional Neural Network increasing, the need for lightweight models to be able to run on embedded devices is also increasing. For that reason, a novel lightweight CNN is designed. Experiment on CIFAR-10 and CIFAR-100 shows that our method outperforms other state-of-the-art models with less parameters and FLOPs.

Original language	English
Title of host publication	2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728132792
DOIs	https://doi.org/10.1109/ICCE-TW46550.2019.8991841
State	Published - May 2019
Event	6th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019 - Yilan, Taiwan Duration: 20 May 2019 → 22 May 2019

Publication series

Name	2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019

Conference

Conference	6th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019
Country/Territory	Taiwan
City	Yilan
Period	20/05/19 → 22/05/19

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10.1109/ICCE-TW46550.2019.8991841

Cite this

Rahadian, F. A., Wahyono, W., Harjoko, A., Wang, J. C., & Wang, C. Y. (2019). CoNet: Compact and Low-Cost CNN for Image Classification. In 2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019 Article 8991841 (2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-TW46550.2019.8991841

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title = "CoNet: Compact and Low-Cost CNN for Image Classification",

abstract = "As the number of applications of Convolutional Neural Network increasing, the need for lightweight models to be able to run on embedded devices is also increasing. For that reason, a novel lightweight CNN is designed. Experiment on CIFAR-10 and CIFAR-100 shows that our method outperforms other state-of-the-art models with less parameters and FLOPs.",

author = "Rahadian, {Fattah Azzuhry} and W. Wahyono and Agus Harjoko and Wang, {Jia Ching} and Wang, {Chien Yao}",

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year = "2019",

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Rahadian, FA, Wahyono, W, Harjoko, A, Wang, JC & Wang, CY 2019, CoNet: Compact and Low-Cost CNN for Image Classification. in 2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019., 8991841, 2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019, Institute of Electrical and Electronics Engineers Inc., 6th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019, Yilan, Taiwan, 20/05/19. https://doi.org/10.1109/ICCE-TW46550.2019.8991841

CoNet: Compact and Low-Cost CNN for Image Classification. / Rahadian, Fattah Azzuhry; Wahyono, W.; Harjoko, Agus et al.
2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8991841 (2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019).

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

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AB - As the number of applications of Convolutional Neural Network increasing, the need for lightweight models to be able to run on embedded devices is also increasing. For that reason, a novel lightweight CNN is designed. Experiment on CIFAR-10 and CIFAR-100 shows that our method outperforms other state-of-the-art models with less parameters and FLOPs.

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PB - Institute of Electrical and Electronics Engineers Inc.

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Rahadian FA, Wahyono W, Harjoko A, Wang JC, Wang CY. CoNet: Compact and Low-Cost CNN for Image Classification. In 2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8991841. (2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019). doi: 10.1109/ICCE-TW46550.2019.8991841

CoNet: Compact and Low-Cost CNN for Image Classification

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