書誌事項
- タイトル別名
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- Development of Real-Time Screening System for Structural Surface Damage Using Object Detection and Generative Model Based on Deep Learning
- シンソウ ガクシュウ ニ モトズク ブッタイ ケンシュツ ト セイセイ モデル オ モチイタ コウゾウ ヒョウメン ソンショウ ノ ジツジカン ケンシュツ ギジュツ ノ カイハツ
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説明
<p>Recently, assessing the integrity of the structures accurately and reliably has become extremely important in various fields in order to increase operational lifetime and improve safety. Detecting surface damage such as cracks, spalling and so on in evaluating the soundness of the structure is particularly important as it is one of the major factors causing deterioration and destruction of the structure. In this study, we develop a real-time screening system for structural surface damage by using object detection technique and generative model based on deep learning. The accuracy of object detection depends largely on the quality and quantity of images given as training data in advance. These images are not kept even by road management companies, etc., and tend to be short. In this study, we generate images of the crack using deep generative model and introduce them into object detection technique. Finally, we investigate whether the detection accuracy of damage is improved by introducing generated images as training data.</p>
収録刊行物
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- 材料
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材料 68 (3), 250-257, 2019-03-15
公益社団法人 日本材料学会
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詳細情報 詳細情報について
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- CRID
- 1390001288129093632
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- NII論文ID
- 130007616718
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- NII書誌ID
- AN00096175
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- ISSN
- 18807488
- 05145163
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- NDL書誌ID
- 029584264
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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サーチ
- Crossref
- CiNii Articles
- OpenAIRE
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- 抄録ライセンスフラグ
- 使用不可
