Recent progresses in machine learning assisted Raman spectroscopy
With the development of Raman spectroscopy and the expansion of its application domains,
conventional methods for spectral data analysis have manifested many limitations. Exploring …
conventional methods for spectral data analysis have manifested many limitations. Exploring …
Trends in extreme learning machines: A review
Extreme learning machine (ELM) has gained increasing interest from various research fields
recently. In this review, we aim to report the current state of the theoretical research and …
recently. In this review, we aim to report the current state of the theoretical research and …
Non-iterative and fast deep learning: Multilayer extreme learning machines
In the past decade, deep learning techniques have powered many aspects of our daily life,
and drawn ever-increasing research interests. However, conventional deep learning …
and drawn ever-increasing research interests. However, conventional deep learning …
Imbalanced fault diagnosis of rolling bearing based on generative adversarial network: A comparative study
Due to the real working conditions and data acquisition equipment, the collected working
data of bearings are actually limited. Meanwhile, as the rolling bearing works in the normal …
data of bearings are actually limited. Meanwhile, as the rolling bearing works in the normal …
What are extreme learning machines? Filling the gap between Frank Rosenblatt's dream and John von Neumann's puzzle
The emergent machine learning technique—extreme learning machines (ELMs)—has
become a hot area of research over the past years, which is attributed to the growing …
become a hot area of research over the past years, which is attributed to the growing …
A hybrid deep learning CNN–ELM for age and gender classification
Automatic age and gender classification has been widely used in a large amount of
applications, particularly in human-computer interaction, biometrics, visual surveillance …
applications, particularly in human-computer interaction, biometrics, visual surveillance …
Multi-kernel extreme learning machine for EEG classification in brain-computer interfaces
One of the most important issues for the development of a motor-imagery based brain-
computer interface (BCI) is how to design a powerful classifier with strong generalization …
computer interface (BCI) is how to design a powerful classifier with strong generalization …
More intelligent and robust estimation of battery state-of-charge with an improved regularized extreme learning machine
Abstract State-of-charge (SOC) is the key parameter for battery management, and the
accurate estimation of SOC is pretty important for the safe and stable operation of lithium …
accurate estimation of SOC is pretty important for the safe and stable operation of lithium …
Extreme learning machine and adaptive sparse representation for image classification
Recent research has shown the speed advantage of extreme learning machine (ELM) and
the accuracy advantage of sparse representation classification (SRC) in the area of image …
the accuracy advantage of sparse representation classification (SRC) in the area of image …
Bayesian network based extreme learning machine for subjectivity detection
Subjectivity detection is a task of natural language processing that aims to remove 'factual'or
'neutral'content, ie, objective text that does not contain any opinion, from online product …
'neutral'content, ie, objective text that does not contain any opinion, from online product …