Drawing understanding from images
Thanks to recent advances in #artificialintelligence and #deeplearning, image recognition has become a reality. #computervision trains machines to interpret and understand the visual world using digital images from cameras and videos. This is combined with deep neural networks that mirror the processes of the human brain.
The capability of machines to recognise and react to images may seem more impressive than it is useful. However, there is a vast and growing range of applications for computer vision across many industries, for example:
#Insurers are using it to categorise #claims, recognise different damage types, estimate repair costs, and decide whether the vehicle should be sent for repair or written off.
In #cancer treatment, computer vision can assess every single "slice" of a CT scan. The technology can recognise nodules from a lung scan before categorising these as benign or malignant. It can also assess the size of the nodule and whether it is reducing, stable or growing.
In #manufacturing, computer vision can automatically detect potential product defects using cameras that monitor the production line. This avoids expensive product recalls.
In the utilities sector, camera drones are helping maintain crucial infrastructure by identifying faulty equipment and fast-growing invasive vegetation. The cameras generate reports automatically. Then engineers can fix the problem instead of spending hours poring over images.
In #retail, brands are applying computer vision to their entire online catalogue. It is embedded in product recommendation engines or even in shop floor cameras that monitor and understand how customers use the retail space.
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