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Multi-View Learning for Material Classification [PDF]
Journal of Imaging, 2022 Material classification is similar to texture classification and consists in predicting the material class of a surface in a color image, such as wood, metal, water, wool, or ceramic. It is very challenging because of the intra-class variability. Indeed,
Borhan Uddin Sumon +3 more
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Incomplete Multi-view Classification via Discriminative and Sparse Representation
Jisuanji kexue yu tansuo, 2021 Generally, the traditional multi-view learning methods assume that all samples are completed in all views. However, this assumption often fails in real applications because of limited access to data, equipment malfunc-tion, as well as occlusion and so on.
XIN Like, YANG Wanqi, YANG Ming
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Fast Multi-view Privileged Random Vector Function Link Network [PDF]
Jisuanji kexue yu tansuo, 2022 In reality, feature data are usually obtained from different ways or levels for the same object, and the data obtained are called multi-view data. It is of research value to mine and utilize multi-view data and shows some advan-tages over traditional ...
WU Tianyu, WANG Shitong
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Multi-view Fuzzy Clustering Combining Visual and Hidden Information with Feature Weighting
Jisuanji kexue yu tansuo, 2021 Multi-view clustering is a type of multi-view learning method applied to unsupervised learning, which aims to use the feature set of different views to enhance the effect of clustering.
LIANG Ling, DENG Zhaohong, WANG Shitong
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Multi-view learning for software defect prediction [PDF]
e-Informatica Software Engineering Journal, 2021 Background: Traditionally, machine learning algorithms have been simply applied for software defect prediction by considering single-view data, meaning the input data contains a single feature vector.
Elife Ozturk Kiyak +2 more
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Multi-view learning-based heterogeneous network representation learning
Journal of King Saud University: Computer and Information Sciences, 2023 Network representation learning is an important tool for extracting latent features from heterogeneous networks to enhance downstream analysis tasks. However, for heterogeneous networks in the era of big data, their heterogeneity, unseen network noises ...
Lei Chen, Yuan Li, Xingye Deng
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Remote Sensing, 2020 This paper introduces a novel multi-view multi-learner (MVML) active learning method, in which the different views are generated by a genetic algorithm (GA).
Nasehe Jamshidpour +2 more
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IMPROVING DEEP LEARNING BASED SEMANTIC SEGMENTATION WITH MULTI VIEW OUTLIER CORRECTION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 The goal of this paper is to use transfer learning for semi supervised semantic segmentation in 2D images: given a pretrained deep convolutional network (DCNN), our aim is to adapt it to a new camera-sensor system by enforcing predictions to be ...
T. Peters, C. Brenner, M. Song
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Recognition of RNA-Binding Protein by Fusion of Multi-view and Multi-label Learning
Jisuanji kexue yu tansuo, 2021 RNA-binding protein (RBP) is a total name of a class of proteins that bind to RNA (ribonucleic acid) along with the process of RNA??s regulation metabolic.
YANG Haitao, DENG Zhaohong, WANG Shitong
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Multi-View Representation Learning via Dual Optimal Transportation
IEEE Access, 2021 Recently, multi-view representation learning has gained rapid growth in various fields. Most of previous multi-view learning methods rely on strong notions of distances that often provide no useful gradients in deep network training, which greatly ...
Peng Li +4 more
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