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Notilyze participated in the SAS EMEA Hackathon 2020. The goal of this Hackathon was to find a way to add sustainable value in real life business. As the connection with data for good was important, the team of Notilyze made a model to extract information from satellite images to help estimating the number of refugees in refugee camps in Nigeria. Better camp size estimation ensures that the demand in each camp can be met easier, as surpluses in goods can be moved to camps with shortages, leading to a more effective cross-camp collaboration. With this case Notilyze ended up winning the first prize.

In the previous article about contrast stretching, we explored percentile contrast stretching and how to apply this to obtain better performance in object detection models. Percentile contrast stretching is also called (histogram) normalization, as we normalize the range of the pixel intensities.

An important part of training neural networks is preprocessing of the input. A lot of performance gain can be obtained by carefully examining, cleaning and transforming the input data.

As stated in our previous post, we are going to make a model to extract information from satellite images to help estimating the number of refugees in refugee camps in Nigeria. In this post we will dive some deeper into this goal. We will answer the questions “How do we want to make this model work?” and “How is this going to help in estimating the number of refugees?”

We proudly announce the participation of Notilyze in the SAS EMEA Hackathon. The Hackathon will take place in February and the goal is to find a way to add sustainable value in real life business. We will take this challenge in cooperation with ELVA Community Engagement and the International Organization for Migration.

In collaboration with the ComplianceAgency, Notilyze is working on a new information security system, so that we can assure you that your data will be and remain safe with us.