As the AI revolution continues, it has been widely predicted that the artistic domain will soon be completely overtaken by machines. In fact, there's already some solid evidence that creative industries such as music, advertising and even film are being transformed by AI—and not just in terms of how we interact with them but also in how they are derived from our interaction with them.
Read more ...Artificial intelligence is an exciting technological frontier for the coral reef remote sensing community, especially the emergence of machine learning algorithms for mapping and detecting features from aerial images of coral reef environments. Machine learning algorithms are finding uses in environmental remote sensing applications that are principally founded on three technological advances: The spatial resolution of remote sensing images has increased incrementally since Earth Observation images were first collected in the late 1960s. Greater detail and smaller features are now visible in coral reef environments. Notably, the widespread use of drone platforms for collecting images at low altitudes above coral reefs has made individual corals visible. What this means is that AI algorithms can detect changes to the health of an ecosystem or determine if an area is being damaged; on the other hand, these algorithms can also help identify areas that are overgrown by coral colonies with ease. The “big data revolution,” refers to the phenomenon of increased capture of earth observation images, which has delivered the information on which artificial intelligence relies to recognize environmental patterns and trends. Global repositories are now continuously updated to provide real-time satellite images, often freely downloadable, for observing coral reefs. A wealth of image-based information is now available for training and evaluating algorithms to interpret coral reefs from above Credit for the first use of a computer for numerical calculation in radiology goes to Dr. Edwin H. Northrop of the Mayo Clinic, who in 1951 showed that computed tomography (CT) scans could detect lung cancer at the early stages of the disease. Since then, this technique has become essential to diagnosis, enabling many people with a variety of cancers to have surgery tailored specifically to their cases.
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