1. Optimal segmentation of high spatial resolution images for the classification of buildings using random forests;M Baatz;Proceedings of the 12 th Symposium for Applied Geographic Information Processing (Angewandte Geographische Informationsverarbeitung XII. AGIT 2000),2000
2. Geographic object-based image analysis towards a new paradigm;T Blaschke;ISPRS J. Photogramm. Remote Sens,2014
3. A multi-scale weakly supervised learning method with adaptive online noise correction for high-resolution change detection of built-up areas;Y Cao;Remote Sens. Environ,2023
4. SegOptim -A new R package for optimizing object-based image analyses of high-spatial resolution remotely-sensed data;J Gon�alves;Int. J. Applied Earth Obs. Geoinf,2019
5. Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set;S Ji;IEEE Trans. Geosci. Remote Sens,2019