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Robustness of Spiking Neural Networks Based on Time-to-First-Spike Encoding Against Adversarial Attacks
http://hdl.handle.net/10228/0002000083
http://hdl.handle.net/10228/0002000083bda39808-1556-4cc4-a821-c694a7205b73
| 名前 / ファイル | ライセンス | アクション |
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neuro_29.pdf (1.9 MB)
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| Item type | 学術雑誌論文 = Journal Article(1) | |||||||||||||||||
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| 公開日 | 2023-09-06 | |||||||||||||||||
| 資源タイプ | ||||||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||||
| タイトル | ||||||||||||||||||
| タイトル | Robustness of Spiking Neural Networks Based on Time-to-First-Spike Encoding Against Adversarial Attacks | |||||||||||||||||
| 言語 | en | |||||||||||||||||
| 言語 | ||||||||||||||||||
| 言語 | eng | |||||||||||||||||
| 著者 |
Nomura, Osamu
× Nomura, Osamu× Sakemi, Yusuke
× Hosomi, Takeo
× 森江, 隆
WEKO
1615
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| 抄録 | ||||||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||||||
| 内容記述 | Spiking neural networks (SNNs) more closely mimic the human brain than artificial neural networks (ANNs). For SNNs, time-to-first-spike (TTFS) encoding, which represents the output values of neurons based on the timing of a single spike, has been proposed as a promising model to reduce power consumption. Adversarial attacks that can lead ANNs to misrecognize images have been reported in many studies. However, the characteristics of TTFS-based SNNs trained using a backpropagation algorithm against adversarial attacks have not yet been clarified. In particular, the dependence of the robustness against adversarial attacks on spike timings has not been investigated. In this brief, we investigated the robustness of SNNs against adversarial attacks and compared it with that of an ANN. We found that SNNs trained with the appropriate temporal penalty settings are more robust against adversarial images than ANNs. | |||||||||||||||||
| 書誌情報 |
en : IEEE Transactions on Circuits and Systems II: Express Briefs 巻 69, 号 9, p. 3640-3644 |
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| 関連タイプ | isIdenticalTo | |||||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||||
| 関連識別子 | https://doi.org/10.1109/TCSII.2022.3184313 | |||||||||||||||||
| ISSN | ||||||||||||||||||
| 収録物識別子タイプ | PISSN | |||||||||||||||||
| 収録物識別子 | 1549-7747 | |||||||||||||||||
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| 収録物識別子タイプ | EISSN | |||||||||||||||||
| 収録物識別子 | 1558-3791 | |||||||||||||||||
| 著作権関連情報 | ||||||||||||||||||
| 権利情報Resource | https://creativecommons.org/licenses/by/4.0/ | |||||||||||||||||
| 権利情報 | IEEE is not the copyright holder of this material. Please follow the instructions via https://creativecommons.org/licenses/by/4.0/ to obtain full-text articles and stipulations in the API documentation. | |||||||||||||||||
| 出版タイプ | ||||||||||||||||||
| 出版タイプ | VoR | |||||||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||||||
| 査読の有無 | ||||||||||||||||||
| 値 | yes | |||||||||||||||||
