{"links":{},"id":2008328,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:02008328","sets":["1164:2036:1771206441417:1771206500162"]},"path":["1771206500162"],"owner":"80578","recid":"2008328","title":["水田におけるアクアドローンを用いた雑草検出"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2026-03-08"},"_buckets":{"deposit":"96c69d80-557d-4146-86a4-d95b42aec308"},"_deposit":{"id":"2008328","pid":{"type":"depid","value":"2008328","revision_id":0},"owners":[80578],"status":"published","created_by":80578},"item_title":"水田におけるアクアドローンを用いた雑草検出","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"水田におけるアクアドローンを用いた雑草検出","subitem_title_language":"ja"},{"subitem_title":"Weed Detection System Using Aqua-Drone in Rice Paddies","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"機械学習とAI","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2026-03-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京農工大学大学院工学府"},{"subitem_text_value":"株式会社NEWGREEN"},{"subitem_text_value":"東京農工大学大学院工学研究院"},{"subitem_text_value":"東京農工大学大学院農学研究院"},{"subitem_text_value":"東京農工大学大学院工学研究院"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Tokyo University of Agriculture and Technology Graduate School of Engineering","subitem_text_language":"en"},{"subitem_text_value":"NEWGREEN Inc.","subitem_text_language":"en"},{"subitem_text_value":"Tokyo University of Agriculture and Technology Institute of Engineering","subitem_text_language":"en"},{"subitem_text_value":"Tokyo University of Agriculture and Technology Institute of Agriculture","subitem_text_language":"en"},{"subitem_text_value":"Tokyo University of Agriculture and Technology Institute of Engineering","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/2008328/files/IPSJ-SLDM26211041.pdf","label":"IPSJ-SLDM26211041.pdf"},"date":[{"dateType":"Available","dateValue":"2028-03-08"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLDM26211041.pdf","filesize":[{"value":"5.1 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"10"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"99a5225a-340f-4948-b7ea-a7b47150fb36","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2026 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"飛鳥,颯舞"}]},{"creatorNames":[{"creatorName":"中村,哲也"}]},{"creatorNames":[{"creatorName":"清水,郁子"}]},{"creatorNames":[{"creatorName":"大川,泰一郎"}]},{"creatorNames":[{"creatorName":"中條,拓伯"}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11451459","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8639","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"田畑における雑草検出では，ニューラルネットワーク(NN)を用いたSemantic Segmentationが活用されているが，従来の上空から撮影した画像データセットでは，作物に隠れた雑草や，水中にある雑草の検出は困難である．本稿では本研究室で2023年度に発表した，稲の間を航行するアクアドローン搭載のカメラから得られた前方画像から，Semantic Segmentationを用いた雑草ピクセルを正確に検出する手法で，アンサンブル学習を行い更なる精度向上を図った．また，NNモデルの学習のための水田雑草画像データセットを示す．複数のSemantic Segmentationモデル，および学習手法でNNの学習をし，比較・評価を行った．その結果，雑草IoU : 0.438, mIoU : 0.704, Pixel Accuracy : 0.970で雑草の検出ができた．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Semantic segmentation based on neural networks (NNs) has been widely used for weed detection in agricultural fields. However, conventional aerial image datasets often fail to detect weeds hidden beneath crops or submerged in water. In this study, we extend our laboratory's 2023 work by applying an ensemble learning approach to further improve the accuracy of weed pixel detection using semantic segmentation on forward-facing images captured by a camera mounted on an aquatic drone navigating between rice plants. We also present a paddy-field weed image dataset developed for training NN models. Multiple semantic segmentation models and training strategies were implemented, compared, and evaluated. Experimental results achieved a weed IoU of 0.438, mIoU of 0.704, and pixel accuracy of 0.970, demonstrating effective weed detection performance.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告システムとLSIの設計技術（SLDM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2026-03-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"41","bibliographicVolumeNumber":"2026-SLDM-211"}]},"relation_version_is_last":true,"weko_creator_id":"80578"},"created":"2026-03-02T10:37:35.267805+00:00","updated":"2026-03-02T10:37:39.080068+00:00"}