書誌事項
- タイトル別名
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- Influence of Pruning Neural Network on Sensitivity Map
- ニューラルネットワーク ノ シ カリ ガ カンド マップ エ オヨボス エイキョウ
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<p>Neural networks have high performance in tasks such as image recognition. However, the computational cost is high, and it is difficult to implement them on small devices. In recent years, in order to solve this problem, research on compression techniques of the neural network has been advanced. “Pruning” is known as one of the important approaches for compression techniques. A “sensitivity map” is a map that visualizes which area of the input data the model focused on. However, it has not been analyzed much on how the model structual changes by pruning affects the sensitivity maps. In this paper, we analyze the influence of pruning on the sensitivity maps. As a result, it was found that the region of interest in the background of the sensitivity map was reduced after pruning.</p>
収録刊行物
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- システム制御情報学会論文誌
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システム制御情報学会論文誌 33 (5), 156-162, 2020-05-15
一般社団法人 システム制御情報学会
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詳細情報 詳細情報について
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- CRID
- 1390285300182505216
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- NII論文ID
- 130007887745
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- NII書誌ID
- AN1013280X
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- ISSN
- 2185811X
- 13425668
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- NDL書誌ID
- 030405045
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
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- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可