@inproceedings{1dd2f4e4f23d45e38ac5ca2165118add,
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}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 6th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019 ; Conference date: 20-05-2019 Through 22-05-2019",
year = "2019",
month = may,
doi = "10.1109/ICCE-TW46550.2019.8991841",
language = "???core.languages.en_GB???",
series = "2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2019",
}