Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2023; 32nd International C Lazaros Iliadis,Antonios Papaleonidas,Chrisina Jay Confe

MEDAL

書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023影響因子(影響力)




書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023影響因子(影響力)學(xué)科排名




書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023網(wǎng)絡(luò)公開度




書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023被引頻次




書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023被引頻次學(xué)科排名




書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023年度引用




書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023年度引用學(xué)科排名




書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023讀者反饋




書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023讀者反饋學(xué)科排名

反應(yīng)

Zusammengesetzte Beanspruchungen,o improve the scalability of the proposal, we propose a distillation-based method to obtain a lightweight model for the rough retrieval stage. The experimental results on the benchmark dataset . show that our approach outperforms the existing works.

Intellectual

Zusammengesetzte Beanspruchungen, that the encryption method achieves satisfactory results. In fact, the performance of some models trained with encrypted data even surpasses that of the unencrypted method, highlighting the effectiveness of the introduced encryption method and partially resolving the problem of data leakage.

幾何學(xué)家

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出來

diathermy

,F-E Fusion: A Fast Detection Method of?Moving UAV Based on?Frame and?Event Flow,the location of moving objects through event flow. Experimental results show that our method has more than 40 times faster recognition speed on the same platform than YOLO v3. The data and the code of the proposed method will be publicly available at

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