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The method first extracts features from the CAD model of a complex part.
Given a rendered image, the proposed method first extracts dominant colors from each object, and represents each object with a dominant color descriptor (DCD).
Given an image I, the method first extracts the keypoints X={x1,…,x n } and their descriptors D={ f1,…,f n }.
This method first extracts the necessary HF components parameters, including time-domain envelopes, frequency-domain envelopes, and energy of the wideband speech; then these parameters are compressed and embedded into the narrowband speech bit stream with a modified watermark technique.
In this paper, the proposed method first extracts the differences between groups of feature words and phrases contained in retweeted text and groups of feature words contained in the tweeting history of users believed to be interested in information from particular Twitter account holders, who are known as followers.
The method first extracts spatial entities as primitives.
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Our method first extracted suspicious MC regions, and then use WSVM to reduce the false positives.
The aforementioned methods first extract the semantics and linked structures from the unstructured datasets and then apply graph theory for network optimization.
In the proposed method, first, we extract MSERs as text candidates with a proper multi-channel and multi-resolution Maximally Stable Extremal Regions (MC MR MSER) strategy.
In our method, we first extract coarse regions of a target using Otsu's method [36].
In this method, we first extract view features from multi-views of 3D models.
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method first trains
method first estimates
method first utilizes
method first selects
method first establishes
method first determines
method first optimizes
method first produces
method first detects
method first converts
method first performs
method first transforms
method first normalizes
method first computes
method first uses
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com