Period Estimation
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Benchmarks
OmniArt
Most implemented
DeepOrientation: convolutional neural network for fringe pattern orientation map estimation
Papers
Physics-Guided Spatiotemporal Learning for Coastal Wave Peak Period Estimation from Video
Wave parameters in the nearshore are crucial for coastal engineering, shoreline protection, marine hazard assessment, and coastal management for climate resilience. Traditional monitoring systems like buoys and radar pla…
Period EstimationTransfer LearningDeepOrientation: convolutional neural network for fringe pattern orientation map estimation
Fringe pattern based measurement techniques are the state-of-the-art in full-field optical metrology. They are crucial both in macroscale, e.g., fringe projection profilometry, and microscale, e.g., label-free quantitati…
DenoisingPeriod EstimationTemporal Graph Signal Decomposition
Temporal graph signals are multivariate time series with individual components associated with nodes of a fixed graph structure. Data of this kind arises in many domains including activity of social network users, sensor…
ImputationMissing ValuesPeriod EstimationTime Series AnalysisGraph Neural Networks for Knowledge Enhanced Visual Representation of Paintings
We propose ArtSAGENet, a novel multimodal architecture that integrates Graph Neural Networks (GNNs) and Convolutional Neural Networks (CNNs), to jointly learn visual and semantic-based artistic representations. First, we…
Art AnalysisMulti-Task LearningPeriod EstimationTAGFast Periodicity Estimation and Reconstruction of hidden components from noisy periodic signal
Periodicity estimation from an arbitrary length noisy signal is computationally very costly. A recently developed Ramanujan Fat Dictionary is one of the ways to find the hidden components from an arbitrary length (non in…
Period EstimationEstimating activity cycles with probabilistic methods I. Bayesian Generalised Lomb-Scargle Periodogram with Trend
Period estimation is one of the central topics in astronomical time series analysis, where data is often unevenly sampled. Especially challenging are studies of stellar magnetic cycles, as there the periods looked for ar…
Period EstimationTime Series Analysis