Condition monitoring and fault diagnosis of induction motor
SK Gundewar, PV Kane - Journal of Vibration Engineering & Technologies, 2021 - Springer
Background An induction motor is at the heart of every rotating machine and hence it is a
very vital component. Almost in every industry, around 90% of the machines apply an …
very vital component. Almost in every industry, around 90% of the machines apply an …
Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions
The explosive growth of data in volume, velocity and diversity that are produced by medical
applications has contributed to abundance of big data. Current solutions for efficient data …
applications has contributed to abundance of big data. Current solutions for efficient data …
Label distribution learning on auxiliary label space graphs for facial expression recognition
Many existing studies reveal that annotation inconsistency widely exists among a variety of
facial expression recognition (FER) datasets. The reason might be the subjectivity of human …
facial expression recognition (FER) datasets. The reason might be the subjectivity of human …
Label enhancement for label distribution learning
Label distribution is more general than both single-label annotation and multi-label
annotation. It covers a certain number of labels, representing the degree to which each label …
annotation. It covers a certain number of labels, representing the degree to which each label …
Uncertainty-aware label distribution learning for facial expression recognition
Despite significant progress over the past few years, ambiguity is still a key challenge in
Facial Expression Recognition (FER). It can lead to noisy and inconsistent annotation, which …
Facial Expression Recognition (FER). It can lead to noisy and inconsistent annotation, which …
A kernel fuzzy c-means clustering-based fuzzy support vector machine algorithm for classification problems with outliers or noises
The support vector machine (SVM) has provided higher performance than traditional
learning machines and has been widely applied in real-world classification problems and …
learning machines and has been widely applied in real-world classification problems and …
Variational label enhancement
Label distribution covers a certain number of labels, representing the degree to which each
label describes the instance. When dealing with label ambiguity, label distribution could …
label describes the instance. When dealing with label ambiguity, label distribution could …
Multi-label feature selection based on correlation label enhancement
Z He, Y Lin, C Wang, L Guo, W Ding - Information Sciences, 2023 - Elsevier
Feature selection is an effective data preprocessing technique that can effectively alleviate
the curse of dimensionality in multi-label learning. The technique selects a subset of features …
the curse of dimensionality in multi-label learning. The technique selects a subset of features …
Geometric algebra applications in geospatial artificial intelligence and remote sensing image processing
With the increasing demand for multidimensional data processing, Geometric algebra (GA)
has attracted more and more attention in the field of geographical information systems. GA …
has attracted more and more attention in the field of geographical information systems. GA …
Generalized label enhancement with sample correlations
Recently, label distribution learning (LDL) has drawn much attention in machine learning,
where LDL model is learned from labelel instances. Different from single-label and multi …
where LDL model is learned from labelel instances. Different from single-label and multi …