{"id":6897,"date":"2020-07-03T12:59:09","date_gmt":"2020-07-03T10:59:09","guid":{"rendered":"https:\/\/nr.no\/?post_type=bc_area&p=6897"},"modified":"2025-08-28T10:48:52","modified_gmt":"2025-08-28T08:48:52","slug":"image-analysis-and-earth-observation","status":"publish","type":"bc_area","link":"https:\/\/nr.no\/en\/areas\/image-analysis-and-earth-observation\/","title":{"rendered":"Image analysis and Earth observation"},"content":{"rendered":"\n
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With close to 40 years of experience, NR has extensive knowledge in image analysis, Earth observation and machine learning, and practical experience with a wide range of applications. Detection, characterisation and object recognition are central themes in many of our projects. <\/p>\n\n\n\n

In addition to object detection, characterisation, recognition and extraction in images and image sequences, we also work with data sequence analysis and pattern recognition of unstructured text. Notably, pattern recognition is not limited to images, but can also be applied to other types of data, such as audio, accoustic signals and written text. Our success often lies in simple, yet efficient solutions using approaches that combine preestablished knowledge and known context with the observed data presented.<\/p>\n\n\n\n

Image analysis<\/h2>\n\n\n\n

Within general image analysis we work in areas like medicine and healthcare, marine, industry and energy. <\/p>\n\n\n\n\n\n

Earth observation<\/h2>\n\n\n\n

Earth observation analyses digital remote sensing data from satellites and aircraft. Furthermore, we develop methods, algorithms and tools for object recognition and classification, as well as size computations based on physical modelling.<\/p>\n\n\n\n\n\n

Deep learning<\/h2>\n\n\n\n

Deep learning, a subset of machine learning, focuses on artificial neural networks and their ability to process and make decisions similarly to the human brain.<\/p>\n\n\n\n

Deep learning has drastically surpassed previous classification methods in terms of accuracy, and it is central in speech recognition, visual object recognition, character recognition, and several language related tasks.<\/p>\n\n\n\n

Deeper machine learning architectures are better at handling complex recognition tasks compared to earlier, shallower models. <\/p>\n\n\n\n

Benefits include:<\/p>\n\n\n\n