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Clearly, visualization by itself will not solve the problem of understanding truly large datasets that would overwhelm both display capacity and the human visual system.
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Different from traditional tree structure represented by a graph with the root node and children nodes from the top to the bottom, Tree Maps proposed by Shneiderman uses circles or rectangles in a 2D space-filling way to delegate a kind of property for a clustered dataset with clearly intuitive visualization [15].
Unlike the traditional approach to represent tree structures by a directed graph with the root node at the top and children nodes below the parent node with lines connecting them, Tree Maps proposed by Shneiderman use a 2D space-filling approach and use circles or rectangles to represent designated properties of molecules for clearly intuitive visualization [30].
Contrast-enhanced ultrasonography clearly improves visualization of the perfusion in various tissues.
The analysis identified several clusters of similar phenotype combinations and allowed for a clearly arranged visualization of our screening results.
In addition, the FFOCM images clearly enable visualization of ganglion cell bodies (arrows in Fig. 2(c)), which are located in the ganglion cell layer.
The visualization clearly justified the efficiency of features learnt by CNN.
Tuft visualization clearly shows that, as the instability evolves, the flow in a given distributor channel suddenly stalls and switches to reverse pumping mode in periodic way.
The feature vector method, combined with PCA for visualization, clearly separates the majority of myoglobins from hemoglobins (fig. 4A), while preserving the ability to identify structural relationships between alpha and beta hemoglobins and leghaemoglobins (fig. 4B).
The visualization clearly shows a structured network.
This visualization clearly highlights the structural differences between both conditions.
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CEO of Professional Science Editing for Scientists @ prosciediting.com