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Multi-view support vector machines with sub-view learning
Multi-view learning improves the performance of existing learning tasks by using complementary information between multiple feature sets. In the...
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Multi-view clustering based on view-attention driven
Multi-view Clustering focuses on discovering coherence information and complementary information about the data among the different views, but often...
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Acoustofluidic scanning fluorescence nanoscopy with a large field of view
Large-field nanoscale fluorescence imaging is invaluable for many applications, such as imaging subcellular structures, visualizing protein...
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Label-noise robust classification with multi-view learning
Label noise is often contained in the training data due to various human factors or measurement errors, which significantly causes a negative effect...
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Dual-attention Network for View-invariant Action Recognition
View-invariant action recognition has been widely researched in various applications, such as visual surveillance and human–robot interaction....
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Consistent multi-view subspace clustering with local structure information
Multi-view subspace clustering has attracted extensive attention in recent years because it can fully utilize the inherent characteristics of each...
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Sequential attention layer-wise fusion network for multi-view classification
Graph convolutional network has shown excellent performance in multi-view classification. Currently, to output a fused node embedding representation...
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Incomplete multi-view clustering via attention-based contrast learning
Multi-view clustering (MVC) is an essential and challenging task in machine learning and data mining. In recent years, this field has attracted a lot...
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Anchor-based sparse subspace incomplete multi-view clustering
In recent decades, multi-view clustering has received a lot of attention. The majority of previous research has assumed that all instances have...
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Class-structure preserving multi-view correlated discriminant analysis for multiblock data
With the rapid development in data acquisition methods, multiple data sources are now becoming available to explain different views of an object....
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A Multi-view Semi-supervised Takagi–Sugeno–Kang Fuzzy System for EEG Emotion Classification
Electroencephalogram (EEG)-based emotion recognition plays an important role in brain-computer interface and mental health monitoring. The large...
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Multi-view subspace clustering based on multi-order neighbor diffusion
Multi-view subspace clustering (MVC) intends to separate out samples via integrating the complementary information from diverse views. In MVC, since...
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Multi-view subspace clustering using drop out technique on points
Multi-view subspace clustering methods have been very popular among all the multi-view clustering approaches. Overall, in the subspace clustering...
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An adaptive weighted self-representation method for incomplete multi-view clustering
For multi-view data in reality, part of its elements may be missing because of human or machine error. Incomplete multi-view clustering (IMC)...
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Multi-view reinforcement learning for sequential decision-making with insufficient state information
Most reinforcement learning methods describe sequential decision-making as a Markov decision process where the effect of action is only decided by...
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A multiple kinds of information extraction method for multi-view low-rank subspace clustering
Recently, multi-view subspace clustering has attracted intensive attentions due to the remarkable clustering performance by extracting abundant...
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MORE: simultaneous multi-view 3D object recognition and pose estimation
Simultaneous object recognition and pose estimation are two key functionalities for robots to safely interact with humans as well as environments....
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Friction modeling from a practical point of view
Regularized static friction models have been used successfully for many years. However, they are unable to maintain static friction in detail. For...
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A robust multi-view knowledge transfer-based rough fuzzy C-means clustering algorithm
Rough fuzzy clustering algorithms have received extensive attention due to the excellent ability to handle overlap** and uncertainty of data....
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Multi-view Feature Learning Based on Texture Description for Palm-Print Recognition
Biometric is the science of validating an individual’s identity while using behavioral and physiological characteristics. In unconstrained scenario,...
