Remote-sensing-CNN-land-classify 遥感landsat 影像地物分类，基于CNN深度学习的方法

A Semantic Segmentation Method for Remote Sensing Images Combining CNN and Transformer.

For the semantic segmentation of remote sensing image, tensorflow implementation

A Tensorflow implentation of light UNet framework for remote sensing semantic segmentation task.

Semantic Segmentation Network with Spatial and Channel Attention Mechanism for High-Resolution Remote Sensing Images

遥感图像的语义分割，分别使用Deeplab V3+(Xception 和mobilenet V2 backbone)和unet模型，keras+python

遥感图像的语义分割，基于深度学习，在Tensorflow框架下，利用TF.Keras，运行环境TF2.0+

The semantic segmentation of remote sensing images

Resources of semantic segmantation based on Deep Learning model

Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

Google Earth Engine App - Tamil Nadu LandUse LandCover classification - Random Forest Classifier

Sample land use classification using an ArcGIS UNet model with the Chesapeake Bay Conservancy data.

We provide a pixel level training dataset for landuse classification (four categories - Green, Water, Barren land and Built up Areas) using google earth engine for India. All associated scripts are…

Based on the deep learning framework (Caffe), the classification of the optical remote sensing image UCMerced LandUse dataset was completed.

分享北京的10wPOI点，字段齐全。

using web crawler obtain the POI information toward specific area is useful. In this repository, I will show a demo obtain Xian and beijing POI information with Baidu map api.

GEE Javascript API scripts to obtain the number of cloudless observations (using Landsat 4, 5, 7, 8 and Sentinel-2)