WEKO3
アイテム
Remote Sensing Image Registration Based on Improved Geometric-Matching CNN
http://hdl.handle.net/10228/0002001544
http://hdl.handle.net/10228/00020015440d0b7fc5-d150-49e9-99da-c620c7c53429
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
LaSEINE-2023_042.pdf (456.4 KB)
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| アイテムタイプ | 共通アイテムタイプ(1) | |||||||||||||||||
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| 公開日 | 2025-04-07 | |||||||||||||||||
| タイトル | ||||||||||||||||||
| タイトル | Remote Sensing Image Registration Based on Improved Geometric-Matching CNN | |||||||||||||||||
| 言語 | en | |||||||||||||||||
| 著者 |
Morishima, Futa
× Morishima, Futa
× 陸, 慧敏
WEKO
15968
× 神谷, 亨
WEKO
402
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| 著作権関連情報 | ||||||||||||||||||
| 権利情報 | Copyright (c) 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||||||||||
| 言語 | en | |||||||||||||||||
| 抄録 | ||||||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||||||
| 内容記述 | Environmental change detection is one of the uses of satellite images. This process is performed by subtracting image pairs obtained by different time series or sensors. Therefore, image registration is an important pre-processing step in detection of environmental changes. Currently, image registration methods based on deep learning are gaining attention. In general, higher satellite image resolution results in more accurate registration. However, the increase in image size leads to higher computational costs during training and estimation of deep learning models. Then, we propose a method that reduces the number of parameters of the model to lower the computational cost while maintaining the accuracy. This method makes it easier to handle high-resolution satellite images. The proposed method modified the GMCNN (Geometric-matching CNN) architecture by adding CSA (Cosine Similarity Attention) and SE (Squeeze-and-Excitation) layers to enhance the feature map, and point-wise convolution to reduce the number of parameters. The improved GMCNN decreases the grid MSE by 0.0037 compared to the conventional GMCNN. It also reduces the number of parameters by 49.6%. | |||||||||||||||||
| 言語 | en | |||||||||||||||||
| 備考 | ||||||||||||||||||
| 内容記述タイプ | Other | |||||||||||||||||
| 内容記述 | 23rd International Conference on Control, Automation and Systems, ICCAS 2023, October 17-20 2023, Yeosu, Korea | |||||||||||||||||
| 言語 | en | |||||||||||||||||
| 書誌情報 |
en : 2023 23rd International Conference on Control, Automation and Systems (ICCAS) p. 1745-1748, 発行日 2023-11-20 |
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| 出版社 | ||||||||||||||||||
| 出版者 | IEEE | |||||||||||||||||
| キーワード | ||||||||||||||||||
| 言語 | en | |||||||||||||||||
| 主題Scheme | Other | |||||||||||||||||
| 主題 | Satellite Image | |||||||||||||||||
| キーワード | ||||||||||||||||||
| 言語 | en | |||||||||||||||||
| 主題Scheme | Other | |||||||||||||||||
| 主題 | Image Registration | |||||||||||||||||
| キーワード | ||||||||||||||||||
| 言語 | en | |||||||||||||||||
| 主題Scheme | Other | |||||||||||||||||
| 主題 | Convolutional Neural Network | |||||||||||||||||
| キーワード | ||||||||||||||||||
| 言語 | en | |||||||||||||||||
| 主題Scheme | Other | |||||||||||||||||
| 主題 | Geometric-matching CNN | |||||||||||||||||
| キーワード | ||||||||||||||||||
| 言語 | en | |||||||||||||||||
| 主題Scheme | Other | |||||||||||||||||
| 主題 | Cosine Similarity Attention | |||||||||||||||||
| 言語 | ||||||||||||||||||
| 言語 | eng | |||||||||||||||||
| 資源タイプ | ||||||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||||
| 出版タイプ | ||||||||||||||||||
| 出版タイプ | AM | |||||||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||||||||
| DOI | ||||||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||||
| 関連識別子 | https://doi.org/10.23919/ICCAS59377.2023.10316818 | |||||||||||||||||
| ISSN | ||||||||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||||||||
| 収録物識別子 | 2642-3901 | |||||||||||||||||
| 会議記述 | ||||||||||||||||||
| 会議名 | 23rd International Conference on Control, Automation and Systems, ICCAS 2023 | |||||||||||||||||
| 言語 | en | |||||||||||||||||
| 回次 | 23 | |||||||||||||||||
| 開始年 | 2023 | |||||||||||||||||
| 開始月 | 10 | |||||||||||||||||
| 開始日 | 17 | |||||||||||||||||
| 終了年 | 2023 | |||||||||||||||||
| 終了月 | 10 | |||||||||||||||||
| 終了日 | 20 | |||||||||||||||||
| 開催地 | Yeosu | |||||||||||||||||
| 言語 | en | |||||||||||||||||
| 開催国 | KOR | |||||||||||||||||
| 査読の有無 | ||||||||||||||||||
| 値 | yes | |||||||||||||||||
| 連携ID | ||||||||||||||||||
| 値 | 14155 | |||||||||||||||||
