Results 41 to 50 of about 169,617 (164)

A Novel Information-based Multi-view Representation Learning

Journal of Applied Science and Engineering
Multi-view representation learning methods achieve great performance in various domains via fusing complementary and consistent information of views, which have gained great attention. However, there still exist two issues in current methods.
Hongdan Wang, Jian Zhang
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View-Driven Multi-View Clustering via Contrastive Double-Learning

Entropy
Multi-view clustering requires simultaneous attention to both consistency and the diversity of information between views. Deep learning techniques have shown impressive abilities to learn complex features when working with extensive datasets; however ...
Shengcheng Liu, Changming Zhu, Zishi Li, Zhiyuan Yang, Wenjie Gu   +4 more
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Multi-view Metric Learning for Multi-view Video Summarization

, 2014
Traditional methods on video summarization are designed to generate summaries for single-view video records; and thus they cannot fully exploit the redundancy in multi-view video records. In this paper, we present a multi-view metric learning framework for multi-view video summarization that combines the advantages of maximum margin clustering with the
Fu, Yanwei, Wang, Lingbo, Guo, Yanwen
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Sharable and Individual Multi-View Metric Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018
This paper presents a sharable and individual multi-view metric learning (MvML) approach for visual recognition. Unlike conventional metric leaning methods which learn a distance metric on either a single type of feature representation or a concatenated representation of multiple types of features, the proposed MvML jointly learns an optimal ...
Junlin Hu, Jiwen Lu, Yap-Peng Tan
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Incremental Data Stream Classification with Adaptive Multi-Task Multi-View Learning

Big Data Mining and Analytics
With the enhancement of data collection capabilities, massive streaming data have been accumulated in numerous application scenarios. Specifically, the issue of classifying data streams based on mobile sensors can be formalized as a multi-task multi-view
Jun Wang, Maiwang Shi, Xiao Zhang, Yan Li, Yunsheng Yuan, Chenglei Yang, Dongxiao Yu   +6 more
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Multi-View Cosine Similarity Learning with Application to Face Verification

Mathematics, 2022
An instance can be easily depicted from different views in pattern recognition, and it is desirable to exploit the information of these views to complement each other.
Zining Wang, Jiawei Chen, Junlin Hu
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A Multi-View Clustering Algorithm for Mixed Numeric and Categorical Data

IEEE Access, 2021
Clustering data with both numeric and categorical attributes is of great importance as such data are ubiquitous in real-world problems. Multi-view learning approaches have proven to be more effective and having better generalisation ability compared to ...
Jinchao Ji, Ruonan Li, Wei Pang, Fei He, Guozhong Feng, Xiaowei Zhao   +5 more
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DeepMVS: Learning Multi-view Stereopsis [PDF]

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018
We present DeepMVS, a deep convolutional neural network (ConvNet) for multi-view stereo reconstruction. Taking an arbitrary number of posed images as input, we first produce a set of plane-sweep volumes and use the proposed DeepMVS network to predict high-quality disparity maps.
Huang, Po-Han, Matzen, Kevin, Kopf, Johannes, Ahuja, Narendra, Huang, Jia-Bin   +4 more
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View-label driven cross-space structure alignment for incomplete multi-view partial multi-label classification

Journal of King Saud University: Computer and Information Sciences
Despite significant advancements in multi-view multi-label learning driven by its broad applicability, real-world scenarios frequently suffer from dual incompleteness in both view and label spaces due to data acquisition uncertainties. The incompleteness
Shenrun Ding, Jiarui Chen, Tongwei Gao, Yinghao Ye, Xiaohuan Lu   +4 more
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Multi-Task Multi-View Learning Based on Cooperative Multi-Objective Optimization

IEEE Access, 2018
Traditional multi-task multi-view (MTMV) models work under the single-objective learning framework and cannot incorporate too many regularization terms, which are primarily attributed to the utilization of the conventional numerical optimization methods.
Di Zhou, Jun Wang, Bin Jiang, Hua Guo, Yajun Li   +4 more
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