Name
Title | ||
|---|---|---|
Geosot Grid Remote Sensing Intelligent Interpretation Model Based On Fine-Tuning Resnet-18: A Case Study Of Construction Land |
Abstract | ||
|---|---|---|
To meet the demand of the real-time monitoring of urban land use, this work establishes a grid-coding index under the framework of a global subdivision grid and constructs a grid remote sensing intelligent interpretation model, based on the fine-tuning ResNet-18 model. The proposed model realizes real-time sharing and query statistics of grid learning results. Setting construction land identification as our objective, SPOT 6 satellite data of September 2018 and Gaofen-1 satellite data of October 2018 were used in an experiment to train and validate the fine-tuning ResNet-18 model. The overall test accuracies of each data set were 97% and 91%, respectively, effectively realizing intelligent change monitoring and distribution statistics with regard to construction land. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/IGARSS39084.2020.9323864 | IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM |
Keywords | DocType | Citations |
Intelligent interpretation, Geo SOT, fine tuning ResNet-18 model, construction land | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daoye Zhu | 1 | 0 | 1.69 |
| Yi Yang | 2 | 0 | 1.01 |
| Weixin Zhai | 3 | 0 | 0.34 |
| Fuhu Ren | 4 | 0 | 1.01 |
| Chengqi Cheng | 5 | 19 | 18.71 |
| Min Huang | 6 | 0 | 0.34 |