Data Science and Satellite Imagery

Data Science and Satellite Imagery

Object detection, sitting at the intersection between Deep Learning and Computer Vision, has recently gained a lot of attention due to its extensive use in multiple real-world applications. International Development is not alien to that trend. In this blog entry, we introduce some of the basic concepts behind the workflow that powers such Artificial Intelligence solutions. For that, we use a real-world application based on satellite imagery from one of our projects at AKTEK.

Contextual awareness is key for the successful implementation of operations, projects and investments in many industries. While field information is still fundamental, collecting that data can be very expensive and may only be possible assuming high risks, especially in fragile and conflict-affected areas. Furthermore, contextual information in such areas becomes outdated very fast, which aggravates those limitations. The rise of object detection techniques, through machine learning and computer vision solutions, is facilitating new applications where images are automatically ingested to inform decision-making processes. This rise has been possible thanks to a combination of factors, the two main ones being the better quality and cost of image recording systems; coupled with the more powerful, but also more affordable, computational resources that power advanced solutions such as deep learning algorithms.

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