The phrase "a set of salient" is correct and usable in written English.
It can be used when referring to a collection of prominent or important features, characteristics, or points in a discussion or analysis.
Example: "In our research, we identified a set of salient factors that influence consumer behavior."
Alternatives: "a collection of key" or "a group of notable".
These representations are not photographic copies or visual images but are more like schematic blueprints that emphasize the arrangement of a set of salient elements, which supply the schema with distinctiveness and differentiate it from similar events.
Facial landmarks are a set of salient points, usually located on the corners, tips or mid points of the facial components.
Other parameters characterizing a conversation at a given point include the domain of discourse, a set of salient perceptible objects, standards of precision, time, world or situation, speaker, and addressee.
The segmentation system creates an HS on the pixels of the input image and an undirected grid graph having hexagons as vertices, and uses this graph in order to produce a set of salient objects contained in the image.
Such a model is described by a set of salient postures ω m, the set of actions A l to be analyzed, transition probabilities a i,j,l from one posture to another for each action A l., transition probabilities of all actions b i,j, and observations emission probabilities p(x/ω m ) for each salient posture ω m.
It is the product of a set of salient beliefs about the consequences of performing the behaviour, each weighted by an evaluation of the importance of the respective consequences.
Figure 6 shows a set of sampled salient points and explains Eq. (2).
The observational learning is solved as a constrained optimization problem, with an objective to generalize from a set of trajectories of salient features in the image space of a vision camera.
Finite element analysis is used only to compute a discrete set of salient circuit parameters, with all other analysis and design computations performed using the networks.
In this image, an observer can plainly see landscape details such as fences, trees, roads, etc. Capturing this same image in the long-wave infrared (i.e., thermal) spectrum provides a different set of salient features (Fig. 1 b).
The stabilization algorithm first identifies a sparse set of salient points, C 1 = { c 1, c 2, c 3,…, c K}, belonging to the subject and/or a fluorescent lymphatic vessel in the reference frame I 1.
