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Moreover, the number and especially the quality of the manually labeled examples challenge such strategies.
Instead of using complex heuristics to define each layer, simple features are defined and machine learning classifiers are trained based on manually labeled examples.
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Kajić et al. introduced a modification of an active appearance model for segmenting macular OCT data, which was trained on a large number of manually labeled example images [ 4].
In machine learning techniques, patterns for identifying relations are not manually written (handcrafted rules) but are learned from labeled examples [71].
They [students] put a lot of effort in building a real training set – they collected 1,500 gesture recordings, each gesture sequenced into 90 frames, and manually labeled from 4,500 to 5,600 examples of each gesture.
Like in other previous work [ 4, 5], our method uses example data (manually labeled scans) to learn from.
An example of a manually labeled B-scan, corresponding to the B-scan in Fig. 4(b), is shown in Fig. 5 (left).
Finally, a custom sentiment model, trained on manually labeled domain-specific tweets, is applied to produce better sentiment classification results.
From manually labeled ground-truth images, we first learn a color model of the elephants.
Initially, the GT regions were manually labeled.
Figure3i is the manually labeled ground-truth.
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