To reconstruct 3D/4D flow from such scattered/incomplete measurements, the author proposed the algorithm of 3D Divergence Free Interpolation from 1D/2D measurements.

Two-dimensional (2D) convolutional neural networks (CNNs) are implemented for machinery fault diagnosis owing to CNN’s capability of feature extraction from input data. One-dimensional (1D) signals ...

This project implements the calculation of similarity for 1D, 2D, and 3D curves, with results ranging from [0, 1]. 1D refers to one-dimensional lines (arrays formed by a series of x coordinates) and ...

In this paper, we compare the performance of the 1D CNN and 2D CNN for the multi-class classification of time-series sensor data. The architecture of each CNN considered in this work has a single ...