European Space Imaging Appoints New Sales Director

European Space Imaging is pleased to announce the appointment of new Sales Director, Pascal Schichor, starting beginning of July 2018.

Pascal has a long standing history with European Space Imaging after first joining the company in 2006 and holding a range of job roles before departing from his role as Sales Manager in early 2017. He is now returning to his roots after having gained extended industry knowledge and experience as Sales Manager Europe, Middle East and Africa at Phase One Industrial, where he was responsible for the overall sales in the Region, directing all sales pursuits and opportunities and managing key accounts reporting to the VP of Sales and the CEO of the Company.

“I am very humbled to be returning to where my career first began and am excited about my new role as Sales Director. European Space Imaging has an excellent reputation within the industry for providing professional and personalised service to their customers and I look forward to once again being a part of that” said Pascal Schichor.

In his role as Sales Director, Pascal will be responsible for implementing the overall sales strategy and increasing offerings to both new and existing businesses. He will oversee the sales team, manage internal and external sales processes as well as the companies strategic business partnerships.

“Pascal has a long history with European Space Imaging. This past experience and knowledge of our customers will be instrumental to enabling us to continue to be the leading imagery provider to all users in Europe ” said Adrian Zevenbergen, European Space Imaging’s Managing Director.

Pascal Schichor rejoins European Space Imaging as Sales Director in July

Share on facebook
Share on twitter
Share on linkedin

Related Stories

Scroll to Top

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.

X