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<p>[QUOTE=&quot;messydesk, post: 3911556, member: 1765&quot;]These really aren&#039;t big challenges.&nbsp; You pick out images that you think have reasonable grades associated with them.&nbsp; That becomes the grading standard that is applied to the network.&nbsp; If you can train a DNN to grade to the standard that you want it to learn, you can train it with a different, similar standard.&nbsp; The challenge is the data.</p><p><br /></p><p>An example of a grading program I&#039;ve seen in action is an application that scores the quality of transthoracic echocardiograms on a scale of 1 to 5.&nbsp; This was used to guide sonographers to make better quality images for cardiologists.&nbsp; Many TTE images had to be used to train the network, and all had to have scores of 1-5 attached to them.&nbsp; In the end, it was quite precise and quite accurate.&nbsp; Compared with grading coins, the amount of data was negligible.&nbsp; One 2D image was assigned one score that said how good the image was.&nbsp; You might get by with this for assigning a details grade to circulated Barber quarters, or perhaps Lincoln cents, but we&#039;re also dealing with more than a 1-5 scale, so the precision of the data will have to be high, as well.[/QUOTE]</p><p><br /></p>

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