Search Results for author:
Found 7 papers, 1 papers with code
Global OpenBuildingMap -- Unveiling the Mystery of Global Buildings
Specifically, if solar panels were placed on the roofs of all buildings, they could supply 1. 1-3. 3 times -- depending on the efficiency of the solar device -- the global energy consumption in 2020, which is the year with the highest consumption on record.
AIO2: Online Correction of Object Labels for Deep Learning with Incomplete Annotation in Remote Sensing Image Segmentation
AIO2 utilizes a mean teacher model to enhance training robustness with noisy labels to both stabilize the training accuracy curve for fitting in ACT and provide pseudo labels for correction in O2C.
Semi-Supervised Building Footprint Generation with Feature and Output Consistency Training
Considering that rich information is also encoded in feature maps, we propose to integrate the consistency of both features and outputs in the end-to-end network training of unlabeled samples, enabling to impose additional constraints.
Instance segmentation of buildings using keypoints
The detected keypoints are subsequently reformulated as a closed polygon, which is the semantic boundary of the building.
Building Footprint Generation by IntegratingConvolution Neural Network with Feature PairwiseConditional Random Field (FPCRF)
Due to the complexity of buildings, the accurate and reliable generation of the building footprint from remote sensing imagery is still a challenging task.
Building Segmentation through a Gated Graph Convolutional Neural Network with Deep Structured Feature Embedding
Taking the semantic segmentation of building footprints as a practical example, we compared different feature embedding architectures and graph neural networks.
Building Footprint Generation Using Improved Generative Adversarial Networks
The automatic generation of building footprints from satellite images presents a considerable challenge due to the complexity of building shapes.
