Results 261 to 270 of about 424,943 (312)

Visualising Deep Network's Time-Series Representations

2021
Despite the popularisation of machine learning models, more often than not, they still operate as black boxes with no insight into what is happening inside the model. There exist a few methods that allow to visualise and explain why a model has made a certain prediction.
Leporowski, B��a��ej, Iosifidis, Alexandros   +1 more
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Time Series Representations

1986
Time series data are usually collected on a monthly, quarterly or annual basis. Such time series provide important economic and demographic information and are published by various institutions on a regular basis.
S. H. C. du Toit, A. G. W. Steyn, R. H. Stumpf   +2 more
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Time series representation for anomaly detection

2009 2nd IEEE International Conference on Computer Science and Information Technology, 2009
Anomaly detection in time series has attracted a lot of attention in the last decade, and is still a hot topic in time series mining. However, time series are high dimensional and feature correlational, directly detecting anomaly patterns in its raw format is very expensive, in addition, different time series may have different lengths of anomaly ...
Mingwei Leng, null Xinsheng Lai, null Guolv Tan, null Xiaohui Xu   +3 more
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Signal2Vec: Time Series Embedding Representation

2019
The rise of Internet-of-Things (IoT) and the exponential increase of devices using sensors, has lead to an increasing interest in data mining of time series. In this context, several representation methods have been proposed. Signal2vec is a novel framework, which can represent any time-series in a vector space.
Christoforos Nalmpantis, Dimitris Vrakas
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Time Series Classification with Representation Ensembles

2015
Time series has attracted much attention in recent years, with thousands of methods for diverse tasks such as classification, clustering, prediction, and anomaly detection. Among all these tasks, classification is likely the most prominent task, accounting for most of the applications and attention from the research community.
Rafael Giusti, Diego F. Silva, Gustavo E. A. P. A. Batista   +2 more
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Text to Time Series Representations: Towards Interpretable Predictive Models

2023
Time Series Analysis (TSA) and Natural Language Processing (NLP) are two domains of research that have seen a surge of interest in recent years. NLP focuses mainly on enabling computers to manipulate and generate human language, whereas TSA identifies patterns or components in time-dependent data.
Mattia Poggioli, Francesco Spinnato, Riccardo Guidotti   +2 more
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A symbolic representation of time series

Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005., 2006
Various representations have been proposed for time series to facilitate similarity searches and discovery of interesting patterns. Although the Euclidean distance and its variants have been most frequently used as similarity measures, they are relatively sensitive to noise and fail to provide meaningful information in many cases.
null Qiang Wang, V. Megalooikonomou, null Guo Li   +2 more
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