書誌事項
- タイトル別名
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- Non-destructive Growth Measurement of Cabbage Plug Seedlings Population by Image Information. (Part 2). Growth Measurement by Neural Network Model.
- ガゾウ ジョウホウ ニ ヨル キャベツセル セイケイ ナエ コタイグン ノ ヒハカイ セイイク ケイソク ダイ2ホウ ニューラル ネットワーク モデル ニ ヨル チジョウブ イクセイ ケイソク
- Growth Measurement by Neural Network Model
- ニューラルネットワークモデルによる地上部生育計測
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抄録
The objective of this study is a non-destructive growth measurement of the plug seedlings population using their image information. In this report, a neural network model for the non-destructive measurement of the leaf area and top fresh weight of the cabbage plug seedlings population was developed. The inputs to the neural network were the relative soil coverage and standard deviation of lightness.<br>The predicted leaf area and top fresh weight of test plug seedlings population based on the neural network model were fitted well with the measured values. Their coefficients of determination R2 were 0.95 and 0.94, respectively. The neural network model give much better result than the soil coverage models reported in the previous report.
収録刊行物
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- 農業機械学会誌
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農業機械学会誌 61 (3), 65-71, 1999
農業食料工学会
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キーワード
詳細情報 詳細情報について
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- CRID
- 1390001204311952768
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- NII論文ID
- 10019113727
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- NII書誌ID
- AN00200470
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- ISSN
- 18846025
- 02852543
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- NDL書誌ID
- 4716698
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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
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可