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10	10	As a general rule, pixel classification is suitable for images in which there are clear differences in the colour, intensity and/ or texture of the feature-of-interest versus the background and other structures.  If there is non-specific labelling in the image that is very similar in appearance to the labelling-of-interest, object classification may allow the non-specific labelling to be filtered out based on object level features such as size and shape. The best approach is determined by trial and error.
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	12	+=== Pixel classification workflow ===
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13		-=== H3 Headings Will Appear In The Table of Content ===
	14	+For a quick introduction, watch: [[https:~~/~~/www.youtube.com/watch?v=5N0XYW9gRZY&feature=youtu.be>>url:https://www.youtube.com/watch?v=5N0XYW9gRZY&feature=youtu.be]]
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15		-==== You can also add images ====
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17		-[[image:Collaboratory.Apps.Article.Code.ArticleSheet@placeholder.jpg]]
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19		-Photo by David Clode
	18	+==== ====
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21		-==== Or code ====
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23		-Code blocks can be added by using the code macro:
24		-
25		-{{code language="python"}}
26		-x = 1
27		-if x == 1:
28		- # indented four spaces
29		- print("x is 1.")
30		-{{/code}}
31		-
32		-(% class="wikigeneratedid" id="HH4Won27tAppearinToC" %)
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