The root of the DSMSFNet network used is at ../networks/deeplab/DSMSFNet.py. Users can adjust the network architecture according to their own needs.
Related comparison methods
| Method | Date | Author | Title | Source | Code |
|---|---|---|---|---|---|
| SVL_3 | 2014 | Gerke M. | Use of the stair vision library within the ISPRS 2D semantic labeling benchmark | Arxiv | None |
| UT_Mev | 2015 | Speldekamp T, Fries C, Gevaert C, et al. | Automatic semantic labelling of urban areas using a rule-based apprOverall Accuracy ch and realized with MeVisLab | Technical Report | None |
| DST_2 | 2016 | Sherrah J. | Fully convolutional networks for dense semantic labelling of high-resolution aerial imagery | Online abstracts of the ISPRS benchmark on urban object classification and 3D building reconstruction | None |
| GSN3 | 2017 | Wang H, Wang Y, Zhang Q, et al. | Gated convolutional neural network for semantic segmentation in high-resolution images | Remote Sensing | None |
| KLab_2 | 2018 | Kemker R, Salvaggio C, Kanan C. | Algorithms for semantic segmentation of multispectral remote sensing imagery using deep learning | ISPRS journal of photogrammetry and remote sensing | Code |
| CVEO | 2018 | Chen G, Zhang X, Wang Q, et al. | Symmetrical dense-shortcut deep fully convolutional networks for semantic segmentation of very-high-resolution remote sensing images | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | None |
| CASDE2 | 2018 | Pan X, Gao L, Marinoni A, et al. | Semantic labeling of high resolution aerial imagery and LiDAR data with fine segmentation network | Remote Sensing | None |
| CONC_4 | 2018 | Forbes T, He Y, Mudur S, et al. | Aggregated residual convolutional neural network for multi-label pixel wise classification of geospatial features | Online abstracts of the ISPRS benchmark on urban object classification and 3D building reconstruction | None |
| ONE_7 | 2018 | Audebert N, Le Saux B, Lefèvre S. | Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks | ISPRS Journal of Photogrammetry and Remote Sensing | None |
| RIT_7 | 2018 | Piramanayagam S, Saber E, Schwartzkopf W, et al. | Supervised classification of multisensor remotely sensed images using a deep learning framework | Remote sensing | None |
| DLR_9 | 2018 | Marmanis D, Schindler K, Wegner J D, et al. | Classification with an edge: Improving semantic image segmentation with boundary detection | ISPRS Journal of Photogrammetry and Remote Sensing | Code |
| CASIA2 | 2018 | Liu Y, Fan B, Wang L, et al. | Semantic labeling in very high resolution images via a self-cascaded convolutional neural network | ISPRS Journal of Photogrammetry and Remote Sensing | Code |
| BUCTY5 | 2019 | Yue K, Yang L, Li R, et al. | TreeUNet: Adaptive tree convolutional neural networks for subdecimeter aerial image segmentation | ISPRS Journal of Photogrammetry and Remote Sensing | Code |
| UFMG_4 | 2019 | Nogueira K, Dalla Mura M, Chanussot J, et al. | Dynamic multicontext segmentation of remote sensing images based on convolutional networks | IEEE Transactions on Geoscience and Remote Sensing | Code |
| HUSTW3 | 2019 | Sun Y, Tian Y, Xu Y. | Problems of encoder-decoder frameworks for high-resolution remote sensing image segmentation: Structural stereotype and insufficient learning | Neurocomputing | None |
| LANet | 2020 | Ding L, Tang H, Bruzzone L. | LANet: Local attention embedding to improve the semantic segmentation of remote sensing images | IEEE Transactions on Geoscience and Remote Sensing | None |
| CGFDN | 2020 | Zhou F, Hang R, Liu Q. | Class-guided feature decoupling network for airborne image segmentation | IEEE Transactions on Geoscience and Remote Sensing | None |
| BAM-UNet-sc | 2021 | Nong Z, Su X, Liu Y, et al. | Boundary-Aware Dual-Stream Network for VHR Remote Sensing Images Semantic Segmentation | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | None |
| MACANet | 2021 | Li X, Lei L, Kuang G. | Multilevel Adaptive-Scale Context Aggregating Network for Semantic Segmentation in High-Resolution Remote Sensing Images | IEEE Geoscience and Remote Sensing Letters | Code |
| SAGNN | 2022 | Diao Q, Dai Y, Zhang C, et al. | Superpixel-based attention graph neural network for semantic segmentation in aerial images | Remote Sensing | None |