The phrase "an input point" is correct and usable in written English.
It can be used in contexts related to data processing, user interfaces, or any situation where a specific point of input is being referenced.
Example: "In the software design, we need to establish an input point for user data to ensure accurate processing."
Alternatives: "a data entry point" or "a user input location".
Our network learns a collection of point function that selects representative/critical points from an input point cloud.
A black line is an input point sequence.
The weight assigned is a function of the distance of an input point from the output cell location.
For segmentation of agglomerates, each image pixel inside the foreground region represents an input point p for clustering.
We first fit an ellipse to an input point sequence and segment the sequence into partial arcs at the intersection points of the fitted ellipse.
In order to segment an input point sequence at intersection points of a fitted ellipse, we fit an ellipse by Fitzgibbon's method.
That is, the system checks whether the coordinate of an input point-match matches the newest point stored in any track or not.
Given a set of n points to be clustered, the agglomerative hierarchical clustering starts with n clusters where each cluster has a single input point with a distance of 0. From there on, the algorithm proceeds in stages.
Then a single input point of each cluster is chosen randomly as a representative and the corresponding I/O pair is inserted into the training set.
This algorithm, specified in Coq, is then automatically extracted into an OCaml program which can be plugged into an interface for data input (point selection) and graphical visualization of the output.
Since the horizontal axis of the residual graph (bar {Q}_{alpha }= alpha, e_{alpha })^{top }) is an index of the input point sequence, the computed error curvature depends on the scale of the horizontal axis of the residual graph.
