JigsawHSI: a network for Hyperspectral Image classification
Fuente:
arXiv
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| Formato: | Preprint |
| Publicado: |
2022
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| _version_ | 1866913654979428352 |
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| author | Moraga, Jaime |
| author_facet | Moraga, Jaime |
| contents | This article describes Jigsaw, a convolutional neural network (CNN) used in geosciences and based on Inception but tailored for geoscientific analyses. Introduces JigsawHSI (based on Jigsaw) and uses it on the land-use land-cover (LULC) classification problem with the Indian Pines, Pavia University and Salinas hyperspectral image data sets. The network is compared against HybridSN, a spectral-spatial 3D-CNN followed by 2D-CNN that achieves state-of-the-art results on the datasets. This short article proves that JigsawHSI is able to meet or exceed HybridSN's performance in all three cases. It also introduces a generalized Jigsaw architecture in d-dimensional space for any number of multimodal inputs. Additionally, the use of jigsaw in geosciences is highlighted, while the code and toolkit are made available. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2206_02327 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | JigsawHSI: a network for Hyperspectral Image classification Moraga, Jaime Computer Vision and Pattern Recognition Machine Learning 68T07 I.4.6; I.2.10 This article describes Jigsaw, a convolutional neural network (CNN) used in geosciences and based on Inception but tailored for geoscientific analyses. Introduces JigsawHSI (based on Jigsaw) and uses it on the land-use land-cover (LULC) classification problem with the Indian Pines, Pavia University and Salinas hyperspectral image data sets. The network is compared against HybridSN, a spectral-spatial 3D-CNN followed by 2D-CNN that achieves state-of-the-art results on the datasets. This short article proves that JigsawHSI is able to meet or exceed HybridSN's performance in all three cases. It also introduces a generalized Jigsaw architecture in d-dimensional space for any number of multimodal inputs. Additionally, the use of jigsaw in geosciences is highlighted, while the code and toolkit are made available. |
| title | JigsawHSI: a network for Hyperspectral Image classification |
| topic | Computer Vision and Pattern Recognition Machine Learning 68T07 I.4.6; I.2.10 |
| url | https://arxiv.org/abs/2206.02327 |