RETRACTED ARTICLE: Machine learning based sign language recognition: a review and its research frontier
R Elakkiya - Journal of Ambient Intelligence and Humanized …, 2021 - Springer
In the recent past, research in the field of automatic sign language recognition using
machine learning methods have demonstrated remarkable success and made momentous …
machine learning methods have demonstrated remarkable success and made momentous …
Adarnn: Adaptive learning and forecasting of time series
Time series has wide applications in the real world and is known to be difficult to forecast.
Since its statistical properties change over time, its distribution also changes temporally …
Since its statistical properties change over time, its distribution also changes temporally …
Sensor classification using convolutional neural network by encoding multivariate time series as two-dimensional colored images
CL Yang, ZX Chen, CY Yang - Sensors, 2019 - mdpi.com
This paper proposes a framework to perform the sensor classification by using multivariate
time series sensors data as inputs. The framework encodes multivariate time series data into …
time series sensors data as inputs. The framework encodes multivariate time series data into …
An effective predictive maintenance framework for conveyor motors using dual time-series imaging and convolutional neural network in an industry 4.0 environment
KS Kiangala, Z Wang - Ieee Access, 2020 - ieeexplore.ieee.org
The ascent of Industry 4.0 and smart manufacturing has emphasized the use of intelligent
manufacturing techniques, tools, and methods such as predictive maintenance. The …
manufacturing techniques, tools, and methods such as predictive maintenance. The …
[HTML][HTML] A novel method for ship carbon emissions prediction under the influence of emergency events
Accurate prediction of ship emissions aids to ensure maritime sustainability but encounters
challenges, such as the absence of high-precision and high-resolution databases, complex …
challenges, such as the absence of high-precision and high-resolution databases, complex …
Reservoir computing approaches for representation and classification of multivariate time series
Classification of multivariate time series (MTS) has been tackled with a large variety of
methodologies and applied to a wide range of scenarios. Reservoir computing (RC) …
methodologies and applied to a wide range of scenarios. Reservoir computing (RC) …
Time works well: Dynamic time warping based on time weighting for time series data mining
H Li - Information Sciences, 2021 - Elsevier
Dynamic time warping is one of the most important similarity measurement methods for time
series data mining. Owing to the different influence of various time points, an extension of …
series data mining. Owing to the different influence of various time points, an extension of …
Multivariate time series classification using dynamic time warping template selection for human activity recognition
Accurate and computationally efficient means for classifying human activities have been the
subject of extensive research efforts. Most current research focuses on extracting complex …
subject of extensive research efforts. Most current research focuses on extracting complex …
Reservoir computing models based on spiking neural P systems for time series classification
H Peng, X Xiong, M Wu, J Wang, Q Yang… - Neural Networks, 2024 - Elsevier
Nonlinear spiking neural P (NSNP) systems are neural-like membrane computing models
with nonlinear spiking mechanisms. Because of this nonlinear spiking mechanism, NSNP …
with nonlinear spiking mechanisms. Because of this nonlinear spiking mechanism, NSNP …
An effective multivariate time series classification approach using echo state network and adaptive differential evolution algorithm
The multivariate time series (MTS) classification is a very difficult process because of the
complexity of the MTS data type. Among all the methods to resolve this problem, the attribute …
complexity of the MTS data type. Among all the methods to resolve this problem, the attribute …