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In this paper, we propose a new knowledge-based method illustrated in the context of segmentation, which labels internal brain structures viewed by magnetic resonance imaging (MRI).
In this paper, the second of two parts, we apply the cost-optimal design method illustrated in Part 1 [1] to a case study.
The integrative method illustrated in this paper is generally applicable to the optimization of architecture in other systems where all the functions are driven by the exergy of the fuel installed onboard.
The method illustrated in this paper – the thermodynamic (constructal) optimization of flow geometry – is applicable to any system that runs on the basis of a limited amount of fuel (exergy) installed onboard, e.g., automobiles, ships, portable tools.
The method illustrated in panel A uses a local measure of brokerage [9].
The mapping method, illustrated in Fig. 1, is based on laser profiling extended to use colour.
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We discuss the results of our approach by making comparisons with previous CNN-based methods illustrated in [3] and [5].
We first examine overall mapping rates and locations of the four methods, illustrated in Figure 1.
The methods illustrated in the previous section are applied to estimate the all-cause mortality risk attributable to temperature, using daily time series from two cities, London and Rome, in the periods 1993-2006 and 1992-2010 respectively.
The reconstruction results by the CoSaMP method and the proposed Bayesian method are illustrated in (c) and (d), respectively.
The configuration of this method is illustrated in Fig. 4 and named as Method II.
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