Algorithms for image analysis are difficult to manage, understand and apply, particularly for non-expert users. For instance, a researcher needs to reduce the noise and improve the contrast in a radiology image prior to analysis and interpretation but is unfamiliar with the specific algorithms that could apply in this instance. In addition, many applications require the processes applied to media to be concisely recorded for re-use, re-evaluation or integration with other analysis data. Quantifying and integrating knowledge, particularly visual outcomes, about algorithms for media is a challenging problem.
Algorithm representation use case
Martinelli M;Salvetti O;Asirelli P
2006
Abstract
Algorithms for image analysis are difficult to manage, understand and apply, particularly for non-expert users. For instance, a researcher needs to reduce the noise and improve the contrast in a radiology image prior to analysis and interpretation but is unfamiliar with the specific algorithms that could apply in this instance. In addition, many applications require the processes applied to media to be concisely recorded for re-use, re-evaluation or integration with other analysis data. Quantifying and integrating knowledge, particularly visual outcomes, about algorithms for media is a challenging problem.File in questo prodotto:
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