Due to its high spatial resolution and reliable global accuracy, we evaluated the suitability of FROM-GLC10 data for understanding agricultural ecosystems in Beijing using a comparable vector data set, Google Earth images and field survey data. The overall accuracy (OA) for FROM-GLC10 based on ...
and important for its application in other fields.The aim of this study was to evaluate the spatial accuracy of the FROM-GLC30 2017 dataset at the national scale and analyze the spatial variation of its accuracy for different land cover types.In our study,the reference land cover data were ...
In this study, the visual interpretation land cover results at 20,936 small watershed sampling units based on high-resolution remote sensing images were used as the reference data covering 65 countries in Asia, Europe, and Africa. The reference data were verified by field survey in typical water...
图2 年度土地覆盖制图结果对比 上述研究成果以“Dual Data- and Knowledge-Driven Land Cover Mapping Framework for Monitoring Annual and Near-Real-Time Changes”(知识与数据双驱动的土地覆盖年度及近实时变化监测框架)为题,发表在IEEE ...
Use of data from the VEGETATION instrument for global environmental monitoring: some lessons from the GLC 2000 and the GBA 2000 projects Daily global mosaics of data acquired by the VEGETATION instrument onboard the SPOT 4 between Nov. 1st, 1999 and Dec. 31st, 2000 have been used to produce...
Characterized by its annual resolution, the dataset meticulously documents the variations in land cover, offering invaluable data for climate change research, ecosystem service assessment, and land use planning. Accessing the Dataset Users have the convenience to download the GLASS-GLC dataset directly f...
The data strongly suggest that this enzyme could be involved in generating branches to central positions of preformed as well as growing polylactosamine chains, but not in synthesizing the distal branches to growing polylactosamine chains.Previous article in issue Next article in issue...
python train_rcnn.py --cfg_file cfgs/default.yaml --batch_size 4 --train_mode rcnn_offline --epochs 30 --ckpt_save_interval 1 --rcnn_training_roi_dir ../output/rpn/default/eval/epoch_200/train_aug/detections/data --rcnn_training_feature_dir ../output/rpn/default/eval/epoch_200/...
Safety Data Hazard Symbols: Properties Molecular Weight:754.645 Density:1.7±0.1 g/cm3 (Predicted) Boiling Point:1177.5±65.0 °C at 760 mmHg (Predicted) Flash Point:665.9±34.3 °C (Predicted) Refractive index:1.679 (Predicted) More Properties>>...
The data logging code is pretty simple and you can modify it to your heart's desire. A better way to generate training data exactly the way you want is by accessing the APIs. This allows you to be in full control of how, what, where and when you want to log data. Computer Vision ...