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- Wan, Bo, et al. Show all 7 Authors
- ISPRS international journal of geo-information 2019 v.8 no.7
- land cover; learning; model validation; remote sensing; uncertainty; vegetation types
- ... Imbalanced learning is a methodological challenge in remote sensing communities, especially in complex areas where the spectral similarity exists between land covers. Obtaining high-confidence classification results for imbalanced class issues is highly important in practice. In this paper, extreme gradient boosting (XGB), a novel tree-based ensemble system, is employed to classify the land cover ...
- Wan, Bo, et al. Show all 6 Authors
- ISPRS international journal of geo-information 2018 v.7 no.12
- algorithms; data collection; roads
- ... The road-network matching method is an effective tool for map integration, fusion, and update. Due to the complexity of road networks in the real world, matching methods often contain a series of complicated processes to identify homonymous roads and deal with their intricate relationship. However, traditional road-network matching algorithms, which are mainly central processing unit (CPU)-based a ...