Homepage / Liste / Contents in : Technical Commission III

Media in this channel :

Categories in this channel

Content with tagdeep learning In the channelTechnical Commission III (8)

Deep learning based on optical flow estimation for change detection: a case study in Indon...

Technical Commission III

1962
Deep learning based on optical flow estimation for change detection: a case study in Indonesia earthquake
Huijiao QIAO

AUTOMATED MARINE OIL SPILL DETECTION USING DEEP LEARNING INSTANCE SEGMENTATION MODEL

Technical Commission III

1629
AUTOMATED MARINE OIL SPILL DETECTION USING DEEP LEARNING INSTANCE SEGMENTATION MODEL
SHAMSUDEEN TEMITOPE YEKEEN

Evaluation of semantic segmentation methods for deforestation detection in the Amazon

Technical Commission III

1202
Evaluation of semantic segmentation methods for deforestation detection in the Amazon
Gilson A O P COSTA

Semantic segmentation of Brazilian Savanna vegetation using high spatial resolution satell...

Technical Commission III

368
Semantic segmentation of Brazilian Savanna vegetation using high spatial resolution satellite data and U-net
Alana Kasahara NEVES

Efficient large-scale Airborne LiDAR data classification via Fully Convolutional Network

Technical Commission III

1359
Efficient large-scale Airborne LiDAR data classification via Fully Convolutional Network
Andrea FUSIELLO

Evaluating a convolutional neural network for feature extraction and tree species classifi...

Technical Commission III

1510
Evaluating a convolutional neural network for feature extraction and tree species classification using UAV-hyperspectral images
Camile SOTHE

Operational pipeline for a global cloud-free mosaic and classification of Sentinel-2 image...

Technical Commission III

1035
Operational pipeline for a global cloud-free mosaic and classification of Sentinel-2 images
MICHAEL SWAINE

Automatically generated training data for land cover classification with cnns using sentin...

Technical Commission III

1000
Automatically generated training data for land cover classification with cnns using sentinel-2 images
Mirjana VOELSEN