Results 41 to 50 of about 128,875 (283)
IEEE Access, 2021 In the hot rolling process, the prediction of strip crown is the key factor to improve the flatness quality of the strip. However, the traditional prediction method can only provide prediction values, but does not quantitatively evaluate the prediction ...
Yan Wu, Xu Li, Feng Luan, Yaodong He
doaj +1 more source
Probabilistic Anomaly Detection in Natural Gas Time Series Data [PDF]
, 2016 This paper introduces a probabilistic approach to anomaly detection, specifically in natural gas time series data. In the natural gas field, there are various types of anomalies, each of which is induced by a range of causes and sources.
Akouemo Kengmo Kenfack, Hermine Nathalie +1 more
core +2 more sources
Onboard Robust Visual Tracking for UAVs Using a Reliable Global-Local Object Model
Sensors, 2016 In this paper, we present a novel onboard robust visual algorithm for long-term arbitrary 2D and 3D object tracking using a reliable global-local object model for unmanned aerial vehicle (UAV) applications, e.g., autonomous tracking and chasing a moving ...
Changhong Fu +3 more
doaj +1 more source
2022 7th International Conference on Smart and Sustainable Technologies (SpliTech), 2022 Detection of anomalies based on smart meter data is crucial to identify potential risks and unusual events at an early stage. The available advanced information and communicating platform and computational capability renders smart grid prone to attacks with extreme social, financial and physical effects.
Johannesen, Nils Jakob +2 more
openaire +2 more sources
Robust PCA as Bilinear Decomposition with Outlier-Sparsity Regularization [PDF]
, 2011 Principal component analysis (PCA) is widely used for dimensionality reduction, with well-documented merits in various applications involving high-dimensional data, including computer vision, preference measurement, and bioinformatics.
Giannakis, Georgios B., Mateos, Gonzalo
core +1 more source
Supervised detection of anomalous light-curves in massive astronomical catalogs
, 2014 The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. To process this information and to extract all possible knowledge, machine learning techniques become ...
Kim, Dae-Won +3 more
core +1 more source
Measuring the Influence of Observations in HMMs through the Kullback-Leibler Distance
, 2012 We measure the influence of individual observations on the sequence of the hidden states of the Hidden Markov Model (HMM) by means of the Kullback-Leibler distance (KLD).
Nuel, Gregory, Perduca, Vittorio
core +1 more source
A Robust Adaptive Stochastic Gradient Method for Deep Learning
, 2017 Stochastic gradient algorithms are the main focus of large-scale optimization problems and led to important successes in the recent advancement of the deep learning algorithms. The convergence of SGD depends on the careful choice of learning rate and the
Bengio, Yoshua +3 more
core +1 more source
FEBS Open Bio, EarlyView.A tri‐culture of iPSC‐derived neurons, astrocytes, and microglia treated with ferroptosis inducers as an Induced ferroptosis model was characterized by scRNA‐seq, cell survival, and cytokine release assays. This analysis revealed diverse microglial transcriptomic changes, indicating that the system captures key aspects of the complex cellular ...
Hongmei Lisa Li +6 more
wiley +1 more source
Automatic Detection of Outliers in Multibeam Echo Sounding Data [PDF]
, 2001 The data volumes produced by new generation multibeam systems are very large, especially for shallow water systems. Results from recent multibeam surveys indicate that the ratio of the field survey time, to the time used in interactive editing through ...
Hou, Tianhang +2 more
core +1 more source