Extraction of characteristics: Location of neighboring pixels in red (on the left); multi-resolution convolution channels (right).</p
After segmentation specific features { , representing the characteristics and properties of the segm...
Top view of the segmentation result for Area 1 (3D-connected regions are denoted using different col...
Top view of the segmentation result for Area 3 (3D-connected regions are denoted using different col...
<p>Scatter plots of the performances of different feature extraction algorithms.</p
The ambiguity in the object detection process can be reduced if the spatial dependencies, which exis...
<p>(A) Based on negative phase contrast image, peaks of light intensity are detected for all cells, ...
<p>Gradient magnitudes and orientations are sampled, and then accumulated into orientation histogram...
Top view of the segmentation result for Area 2 (3D-connected regions are denoted using different col...
Examples of features extracted from two different images: (a) original images, (b) gradient, and (c)...
<p>All textural features were extracted separately for red, green, and blue color channels.</p
<p>All textural features were extracted separately for red, green, and blue color channels from the ...
Coloured regions can be segregated from each other by using colour-opponent mechanisms, colour contr...
The details of the features processed by three levels of feature selection methods.</p
The convovlved images of a bin area with laws masks (A) L5E5, (B) E5S5, (C) R5R5, and (D) L5S5.</p
<p>(a) Feature maps from different samples of ear A. (b) Feature maps from different samples of ear ...
After segmentation specific features { , representing the characteristics and properties of the segm...
Top view of the segmentation result for Area 1 (3D-connected regions are denoted using different col...
Top view of the segmentation result for Area 3 (3D-connected regions are denoted using different col...
<p>Scatter plots of the performances of different feature extraction algorithms.</p
The ambiguity in the object detection process can be reduced if the spatial dependencies, which exis...
<p>(A) Based on negative phase contrast image, peaks of light intensity are detected for all cells, ...
<p>Gradient magnitudes and orientations are sampled, and then accumulated into orientation histogram...
Top view of the segmentation result for Area 2 (3D-connected regions are denoted using different col...
Examples of features extracted from two different images: (a) original images, (b) gradient, and (c)...
<p>All textural features were extracted separately for red, green, and blue color channels.</p
<p>All textural features were extracted separately for red, green, and blue color channels from the ...
Coloured regions can be segregated from each other by using colour-opponent mechanisms, colour contr...
The details of the features processed by three levels of feature selection methods.</p
The convovlved images of a bin area with laws masks (A) L5E5, (B) E5S5, (C) R5R5, and (D) L5S5.</p
<p>(a) Feature maps from different samples of ear A. (b) Feature maps from different samples of ear ...
After segmentation specific features { , representing the characteristics and properties of the segm...
Top view of the segmentation result for Area 1 (3D-connected regions are denoted using different col...
Top view of the segmentation result for Area 3 (3D-connected regions are denoted using different col...
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