書誌事項
- タイトル別名
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- Research Concerning Recursive Active Learning for Segmentation of Automobile Parts
抄録
<p>In traffic census, it is expected to develop image processing technologies for counting number of passing automobiles by analyzing video image. Many counting technologies using deep learning have been proposed. It is difficult to maintain sufficient accuracy because new automobiles are sold year after year. Therefore, it is necessary to maintain high accuracy by re-learning training data of automobiles with new shapes and colors continuously. However, maintenance labor cost is huge because training data have to be created continuously. In this research, technique to recursive active learning for segmentation of automobile parts is proposed and clarified its usefulness.</p>
収録刊行物
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- 写真測量とリモートセンシング
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写真測量とリモートセンシング 62 (1), 4-21, 2023
一般社団法人 日本写真測量学会
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詳細情報 詳細情報について
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- CRID
- 1390017843891427200
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- ISSN
- 18839061
- 02855844
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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
- Crossref
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- 抄録ライセンスフラグ
- 使用不可