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AI Chain from Geo4i

The AI Chain from Geo4i is a GEOINT & IMINT API environment for the automatic detection of generic objects in satellite images. The product can be integrated into GeoSpace and is based on TensorFlow, tailored to fit D&I needs. The training set is generated by the user’s imagery and the

Aleph-1 Constellation

The Aleph-1 constellation from Satellogic offers European Space Imaging customers the “sweet spot” of collecting data with enough clarity to extract meaningful insights at a revisit frequency and cost that is competitive within the industry. The total constellation of 300 planned satellites delivers sub-meter multispectral and 25 m hyperspectral imagery

Amatrice, Italy, Before and After the Quake

On hearing about the earthquake early this morning European Space Imaging’s satellite tasking operations team managed to collect the first satellite image of the damage at 10:21 am (UTC). If you compare it to the high-resolution satellite image taken on the 9th August 2010 you can clearly see the effects

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Architecture of ResNet34-UNet model

UNet architecture for semantic segmentation with ResNet34 as encoder or feature extraction part. ResNet34 is used as an encoder or feature extractor in the contracting path and the corresponding symmetric expanding path predicts the dense segmentation output.

Architecture of VGG16-UNet model

UNet architecture for semantic segmentation with VGG16 as the encoder or feature extractor. VGG16 is used as an encoder or feature extractor in the contracting path and the corresponding symmetric expanding path predicts the dense segmentation output.

Architecture of ResNet34-FCN model

In this model, ResNet34 is used for feature extraction and the FCN operation remains as is. The feature of ResNet architecture is exploited where just like VGG, as the number of filters double, the feature map size gets halved. This gives a similarity to VGG and ResNet architecture while supporting deeper architecture and addressing the issue of vanishing gradients while also being faster. The fully connected layer at the output of ResNet34 is not used and instead converted to fully convolutional layer by means of 1×1 convolution.

Architecture of VGG16-FCN model

In this model, VGG16 is used for feature extraction which also performs the function of an encoder. The fully connected layer of the VGG16 is not used and instead converted to fully convolutional layer by means of 1×1 convolution.

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