Sentence examples for an advanced classification from inspiring English sources

Despite of the previously done comparisons between natural product compounds and synthetic ones, here we present a general comparison of all elements and atom types for an advanced classification of compounds from different resources.

Additionally though, we implemented an advanced classification for stage 2 and onwards, where capillary non-perfusion was evaluated separately for each of four quadrants of the retina, based on WFA findings with the Straurenghi 230 scanning laser ophthalmoscope retina lens (Ocular Instruments, Glenfield, Auckland).

However, a more advanced classification may further specify illness course (episodic, chronic with increasing impairment, chronic with stable impairment, etc.

This represents a challenge, as advanced classification techniques are required to separate the different conformations into structurally homogeneous subsets that are amenable to single-particle reconstruction (Scheres et al., 2007; Fischer et al., 2010).

It has introduced an advanced handover classification system as well as new concepts such as network dwell time (NDT), time before handover (TBH) and exit time (ET) [12].

Four of the current most advanced classification methods are used to discriminate among the psychiatric conditions and leave-one-out cross-validation is used to evaluate the classifiers.

The SPIN project is focused on the development and testing of advanced classification methods and spatial indicators based on multisensor satellite data and GIS to accomplish monitoring and management tasks in the context of Natura 2000 and nature conservation.

Moreover, more advanced classification methods will be investigated.

While we can not rule out that more advanced classification methodologies and/or better distance metrics might be applicable in order to improve prediction accuracy, it is quite interesting and exciting that standard, simple methods are quite accurate and useful.

Many advanced classification techniques have been developed for machine learning.

In addition, more advanced classification algorithms and techniques will be considered, including advanced artificial neural network architectures, such as higher order and spiking neural networks.