Fully Convolutional Siamese Networks for Change Detection
This paper presents three fully convolutional neural network architectures which perform change detection using a pair of coregistered images. Most notably, we propose two Siamese extensions of fully convolutional networks which use heuristics about the current problem to achieve the best results in...
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| Published in: | Proceedings - International Conference on Image Processing pp. 4063 - 4067 |
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| Main Authors: | , , |
| Format: | Conference Proceeding |
| Language: | English |
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IEEE
01.10.2018
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| ISSN: | 2381-8549 |
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| Abstract | This paper presents three fully convolutional neural network architectures which perform change detection using a pair of coregistered images. Most notably, we propose two Siamese extensions of fully convolutional networks which use heuristics about the current problem to achieve the best results in our tests on two open change detection datasets, using both RGB and multispectral images. We show that our system is able to learn from scratch using annotated change detection images. Our architectures achieve better performance than previously proposed methods, while being at least 500 times faster than related systems. This work is a step towards efficient processing of data from large scale Earth observation systems such as Copernicus or Landsat. |
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| AbstractList | This paper presents three fully convolutional neural network architectures which perform change detection using a pair of coregistered images. Most notably, we propose two Siamese extensions of fully convolutional networks which use heuristics about the current problem to achieve the best results in our tests on two open change detection datasets, using both RGB and multispectral images. We show that our system is able to learn from scratch using annotated change detection images. Our architectures achieve better performance than previously proposed methods, while being at least 500 times faster than related systems. This work is a step towards efficient processing of data from large scale Earth observation systems such as Copernicus or Landsat. |
| Author | Boulch, Alexandre Caye Daudt, Rodrigo Le Saux, Bertr |
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| Snippet | This paper presents three fully convolutional neural network architectures which perform change detection using a pair of coregistered images. Most notably, we... |
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| SubjectTerms | Cats Change detection Change detection algorithms Computer architecture Earth Earth observation fully convolutional networks Image analysis Machine learning supervised machine learning Training |
| Title | Fully Convolutional Siamese Networks for Change Detection |
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