Image search using multiple semantic labels Once the semantic models were trained, database images could be searched based on their relevance scores of multiple morphology semantics.
To prevent "over fitting", when Minwa's mathematical model becomes too obsessed with the specifics of the portion of images it is trained on, the data is also supplied in skewed forms, with vignetting, cropping, colour and shape distortion all applied to make sure the model only learns the important characteristics of the image subject.
Nielsen et al. [ 28] describe an algorithm that extracts textural information from all pixels of segmented breast images, which is "trained" to recognize texture relating to breast cancer status of the women.
However, the first two patches were training images used to get the user comfortable with the validation system and are not counted in the final result.
Within those images, the subject was trained to show their emotions in three different gaze directions.
Based on a number of points in a set of images, an SSM is trained by applying principal component analysis to the aligned shapes [24].
Using fast Rcnn Caffe, the deep learning of numerous tower images of transmission line is trained, and the image features of the transmission tower is extracted.
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In multivariate image analysis, a classifier is trained using features from cells known to be from the two classes to be separated.
Multi-class SVMs are trained for images belonging to each vessel type and classification is done.
On the age front, Rothe says it was trained on images from IMDb and Wikipedia — along with "some other smaller datasets".
