Modeling multi-variate time-series (MVTS) data is a long-standing research subject and has found wide applications. Recently, there surge of interest in modeling spatial relations between variables as graphs, i.e., first learning one static graph for each dataset then exploiting the structure via neural networks. However, may differ substantially across samples, building all samples inherently ...

Cross-model retrieval has emerged as one of the most important upgrades for text-only search engines (SE). Recently, with powerful representation pairwise text–image inputs via early interaction, accuracy vision–language (VL) transformers outperformed existing methods retrieval. However, when same paradigm is used inference, efficiency VL still too low to be applied in a real cross-modal SE. In...

Estimating the gravity anomaly causative bodies boundary can facilitate the gravity field interpretation. In this paper, 2D discrete wavelet transform (DWT) is employed as a method to delineate the boundary of the gravity anomaly sources. Hence, the GRACE’ satellite gravity data is decomposed using DWT. DWT decomposites a single approximation coefficients into four distinct components: the appr...

In many signal processing applications, such as EEG analysis, the non-stationary signal is often required to be segmented into small epochs. This is accomplished by drawing the boundaries of signal at time instances where its statistical characteristics, such as amplitude and/or frequency, change. In the proposed method, the original signal is initially decomposed into signals with different fr...