Results 21 to 30 of about 24,544,958 (149)

Multiview clustering method for view-unaligned data

Tongxin xuebao, 2022
A new challenge for multi-view learning was posed by corrupted view-correspondences.To address this issue， an effective multi-view learning method for view-unaligned data was proposed.First，to capture cross-view latent affinity in multi-view heterogenous
Ao LI, Cong FENG, Yutong NIU, Shibiao XU, Yingtao ZHANG, Guanglu SUN   +5 more
doaj   +2 more sources

Multi-view audio and music classification

, 2021
We propose in this work a multi-view learning approach for audio and music classification. Considering four typical low-level representations (i.e. different views) commonly used for audio and music recognition tasks, the proposed multi-view network ...
Ian McLoughlin (10759890), Oliver Y. Chén (18293890), Huy Le Nguyen, Mertins, A, Pham, L, McLoughlin, I, Le Nguyen, H, Huy Phan, Philipp Koch (147348), Alfred Mertins, Huy Le Nguyen (18293870), Lam Pham (12154865), Lam Pham, Koch, P, Ian McLoughlin, Alfred Mertins (6695471), Oliver Y. Chen, Huy Phan (4427185), Chén, OY, Phan, H, Philipp Koch   +20 more
core   +1 more source

Multi-View Classification via a Fast and Effective Multi-View Nearest-Subspace Classifier

IEEE Access, 2019
Multi-view data represented in multiple views contains more complementary information than a single view, whereby multi-view learning explores and utilizes the multi-view data.
Ting Shu, Bob Zhang, Yuan Yan Tang
doaj   +1 more source

A Novel H.264/AVC Based Multi-View Video Coding Scheme [PDF]

, 2008
This paper investigates extensions of H.264/AVC for compressing multi-view video sequences. The proposed technique re-sorts frames of sequences captured by multiple cameras looking at a person in a scene from different views and generates a single video ...
Akbari, S, Redmill, DW, Agrafiotis, D, Canagarajah, CN, Bull, DR   +4 more
core   +1 more source

On surrogate supervision multi-view learning [PDF]

Data can be represented in multiple views. Traditional multi-view learning methods (i.e., co-training, multi-task learning) focus on improving learning performance using information from the auxiliary view, although information from the target view is ...
Jin, Gaole
core   +6 more sources

Multi-View Spectral Clustering via ELM-AE Ensemble Features Representations Learning

IEEE Access, 2020
Spectral cluster based on multi-view data has proven effective for clustering multi-source real-world data because consensus and complementary information of multi-view data ensure the result of clustering.
Lijuan Wang, Shifei Ding
doaj   +1 more source

A review of multi-instance learning assumptions [PDF]

, 2010
Multi-instance (MI) learning is a variant of inductive machine learning, where each learning example contains a bag of instances instead of a single feature vector.
Frank, Eibe, Foulds, James Richard
core   +1 more source

Exploring Dynamic Hierarchical Fusion for Multi-View Clustering

IEEE Access
Multi-view clustering is effective at uncovering the latent structures within different views or modalities. However, existing approaches often oversimplify the problem by treating the contribution and granularity of information from all views as uniform,
Zhenshan Chen, Xuran Tian, Lizhen Gao, Gengbin Liao, Yang Shen, Kainan Zheng, Jianglin Fang   +6 more
doaj   +1 more source

multiviewstacking: A Python Package for Training Multi-View Stacking Classifiers

Journal of Open Research Software
The multiviewstacking Python package provides an open-source implementation of the Multi-View Stacking (MVS) algorithm for supervised classification tasks.
Enrique Garcia-Ceja
doaj   +1 more source

Multi-View Based Multi-Model Learning for MCI Diagnosis

Brain Sciences, 2020
Mild cognitive impairment (MCI) is the early stage of Alzheimer’s disease (AD). Automatic diagnosis of MCI by magnetic resonance imaging (MRI) images has been the focus of research in recent years. Furthermore, deep learning models based on 2D view
Ping Cao, Jie Gao, Zuping Zhang
doaj   +1 more source