Complete Model for Automatic Object Detection and Localisation on Aerial Images using Convolutional Neural Networks
In this paper, a novel approach for an automatic object detection and localisation on aerial images is proposed. Proposed model does not use ground control points (GCPs) and consists of three major phases. In the first phase, optimal flight route is planned in order to capture the area of interest a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Croatian Communications and Information Society (CCIS)
2018-03-01
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| Series: | Journal of Communications Software and Systems |
| Subjects: | |
| Online Access: | https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/441 |
| _version_ | 1819040492142198784 |
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| author | Dunja Božić-Štulić Stanko Kružić Sven Gotovac Vladan Papić |
| author_facet | Dunja Božić-Štulić Stanko Kružić Sven Gotovac Vladan Papić |
| author_sort | Dunja Božić-Štulić |
| collection | DOAJ |
| description | In this paper, a novel approach for an automatic object detection and localisation on aerial images is proposed. Proposed model does not use ground control points (GCPs) and consists of three major phases. In the first phase, optimal flight route is planned in order to capture the area of interest and aerial images are acquired using unmanned aerial vehicle (UAV), followed by creating a mosaic of collected images to obtained larger field-of-view panoramic image of the area of interest and using the obtained image mosaic to create georeferenced map. The image mosaic is then also used to detect objects of interest using the approach based on convolutional neural networks. |
| first_indexed | 2024-12-21T09:09:57Z |
| format | Article |
| id | doaj.art-a05e960e5e7f405481e0f7d801b23727 |
| institution | Directory Open Access Journal |
| issn | 1845-6421 1846-6079 |
| language | English |
| last_indexed | 2024-12-21T09:09:57Z |
| publishDate | 2018-03-01 |
| publisher | Croatian Communications and Information Society (CCIS) |
| record_format | Article |
| series | Journal of Communications Software and Systems |
| spelling | doaj.art-a05e960e5e7f405481e0f7d801b237272022-12-21T19:09:14ZengCroatian Communications and Information Society (CCIS)Journal of Communications Software and Systems1845-64211846-60792018-03-011418290Complete Model for Automatic Object Detection and Localisation on Aerial Images using Convolutional Neural NetworksDunja Božić-ŠtulićStanko KružićSven GotovacVladan PapićIn this paper, a novel approach for an automatic object detection and localisation on aerial images is proposed. Proposed model does not use ground control points (GCPs) and consists of three major phases. In the first phase, optimal flight route is planned in order to capture the area of interest and aerial images are acquired using unmanned aerial vehicle (UAV), followed by creating a mosaic of collected images to obtained larger field-of-view panoramic image of the area of interest and using the obtained image mosaic to create georeferenced map. The image mosaic is then also used to detect objects of interest using the approach based on convolutional neural networks.https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/441georeferencingGISUAVimage mosaicobject detectionconvoloutional neural networks |
| spellingShingle | Dunja Božić-Štulić Stanko Kružić Sven Gotovac Vladan Papić Complete Model for Automatic Object Detection and Localisation on Aerial Images using Convolutional Neural Networks Journal of Communications Software and Systems georeferencing GIS UAV image mosaic object detection convoloutional neural networks |
| title | Complete Model for Automatic Object Detection and Localisation on Aerial Images using Convolutional Neural Networks |
| title_full | Complete Model for Automatic Object Detection and Localisation on Aerial Images using Convolutional Neural Networks |
| title_fullStr | Complete Model for Automatic Object Detection and Localisation on Aerial Images using Convolutional Neural Networks |
| title_full_unstemmed | Complete Model for Automatic Object Detection and Localisation on Aerial Images using Convolutional Neural Networks |
| title_short | Complete Model for Automatic Object Detection and Localisation on Aerial Images using Convolutional Neural Networks |
| title_sort | complete model for automatic object detection and localisation on aerial images using convolutional neural networks |
| topic | georeferencing GIS UAV image mosaic object detection convoloutional neural networks |
| url | https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/441 |
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